ELLIS contributions to NeurIPS 2023

The NeurIPS conference is an annual highlight for the global machine learning research community. This year, it takes place from 10 - 16 December 2023 in New Orleans (USA). It is an opportunity for scientists to present and discuss the latest cutting-edge AI research and to connect with peers.

Out of all conference contributions, around 500 include contributions from ELLIS members. The following list provides an overview and highlights the names of ELLIS members in bold.

If your contirbution or name is missing here, feel free to inform us via pr@ellis.eu.

NeurIPS 2023 poster

#	Paper Title	List of authors (ELLIS members in bold)
1	What is Flagged in Uncertainty Quantification? Latent Density Models for Uncertainty Categorization	Hao Sun, Boris van Breugel, Jonathan Crabbé, Nabeel Seedat, Mihaela van der Schaar
2	Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning	Yu Wang, Zhun Zhong, Pengchong Qiao, Xuxin Cheng, Xiawu Zheng, Chang Liu, Nicu Sebe, Rongrong Ji, Jie Chen
3	The Crucial Role of Normalization in Sharpness-Aware Minimization	Yan Dai, Kwangjun Ahn, Suvrit Sra
4	Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions	Çağlar Hızlı, S. T. John, Anne Tuulikki Juuti, Tuure Tapani Saarinen, Kirsi Hannele Pietiläinen, Pekka Marttinen
5	Universality and Limitations of Prompt Tuning	Yihan Wang, Jatin Chauhan, Wei Wang, Cho-Jui Hsieh
6	Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints	Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers
7	Automated Classification of Model Errors on ImageNet	Momchil Peychev, Mark Niklas Mueller, Marc Fischer, Martin Vechev
8	A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence	Carlo Alfano, Rui Yuan, Patrick Rebeschini
9	What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?	Fnu Suya, Xiao Zhang, Yuan Tian, David Evans
10	Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games	Brian Hu Zhang, Gabriele Farina, Ioannis Anagnostides, Federico Cacciamani, Stephen Marcus McAleer, Andreas Alexander Haupt, Andrea Celli, Nicola Gatti, Vincent Conitzer, Tuomas Sandholm
11	Expressivity-Preserving GNN Simulation	Fabian Jogl, Maximilian Thiessen, Thomas Gärtner
12	Covariance-adaptive best arm identification	El Mehdi Saad, Gilles Blanchard, Nicolas Verzelen
13	Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension	Moritz Haas, David Holzmüller, Ulrike von Luxburg, Ingo Steinwart
14	Star-Shaped Denoising Diffusion Probabilistic Models	Andrey Okhotin, Dmitry Molchanov, Arkhipkin Sergeevich Vladimir, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, Dmitry P. Vetrov
15	What Can We Learn from Unlearnable Datasets?	Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
16	SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities	Hugues Van Assel, Titouan Vayer, Rémi Flamary, Nicolas Courty
17	Learning Causal Models under Independent Changes	Sarah Mameche, David Kaltenpoth, Jilles Vreeken
18	Color Equivariant Convolutional Networks	Attila Lengyel, Ombretta Strafforello, Robert-Jan Bruintjes, Alexander Gielisse, Jan van Gemert
19	Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression	Youngsoo Baek, Samuel Berchuck, Sayan Mukherjee
20	Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks	Steven Adriaensen, Herilalaina Rakotoarison, Samuel Müller, Frank Hutter
21	Towards Data-Agnostic Pruning At Initialization: What Makes a Good Sparse Mask?	Hoang Pham, The-Anh Ta, Shiwei Liu, Lichuan Xiang, Dung D. Le, Hongkai Wen, Long Tran-Thanh
22	Practical Equivariances via Relational Conditional Neural Processes	Daolang Huang, Manuel Haussmann, Ulpu Remes, S. T. John, Grégoire Clarté, Kevin Sebastian Luck, Samuel Kaski, Luigi Acerbi
23	For SALE: State-Action Representation Learning for Deep Reinforcement Learning	Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Shane Gu, Doina Precup, David Meger
24	The Tunnel Effect: Building Data Representations in Deep Neural Networks	Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Miłos ́, Tomasz Trzcinski
25	Optimal Algorithms for the Inhomogeneous Spiked Wigner Model	Alexander Pak, Justin Ko, Florent Krzakala
26	LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching	Duy Minh Ho Nguyen, Hoang Nguyen, Nghiem Tuong Diep, Tan Ngoc Pham, Tri Cao, Binh T. Nguyen, Paul Swoboda, Nhat Ho, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag, Mathias Niepert
27	Do Not Marginalize Mechanisms, Rather Consolidate!	Moritz Willig, Matej Zečević, Devendra Singh Dhami, Kristian Kersting
28	Taming Local Effects in Graph-based Spatiotemporal Forecasting	Andrea Cini, Ivan Marisca, Daniele Zambon, Cesare Alippi
29	BayesDAG: Gradient-Based Posterior Inference for Causal Discovery	Yashas Annadani, Nick Pawlowski, Joel Jennings, Stefan Bauer, Cheng Zhang, Wenbo Gong
30	Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships	Abhra Chaudhuri, Massimiliano Mancini, Zeynep Akata, Anjan Dutta
31	Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability	Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis
32	Compositional Sculpting of Iterative Generative Processes	Timur Garipov, Sebastiaan De Peuter, Ge Yang, Vikas Garg, Samuel Kaski, Tommi S. Jaakkola
33	GAUCHE: A Library for Gaussian Processes in Chemistry	Ryan-Rhys Griffiths, Leo Klarner, Henry Moss, Aditya Ravuri, Sang T. Truong, Yuanqi Du, Samuel Don Stanton, Gary Tom, Bojana Ranković, Arian Rokkum Jamasb, Aryan Deshwal, Julius Schwartz, Austin Tripp, Gregory Kell, Simon Frieder, Anthony Bourached, Alex James Chan, Jacob Moss, Chengzhi Guo, Johannes P. Dürholt, Saudamini Chaurasia, Ji Won Park, Felix Strieth-Kalthoff, Alpha Lee, Bingqing Cheng, Alan Aspuru-Guzik, Philippe Schwaller, Jian Tang
34	Structured Voronoi Sampling	Afra Amini, Li Du, Ryan Cotterell
35	PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning	Neeratyoy Mallik, Eddie Bergman, Carl Hvarfner, Danny Stoll, Maciej Janowski, Marius Lindauer, Luigi Nardi, Frank Hutter
36	Minimax Forward and Backward Learning of Evolving Tasks with Performance Guarantees	Veronica Alvarez, Santiago Mazuelas, Jose A. Lozano
37	Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling	Zhenyu Zhu, Francesco Locatello, Volkan Cevher
38	(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability	Mathieu Even, Scott Pesme, Suriya Gunasekar, Nicolas Flammarion
39	Knowledge Distillation Performs Partial Variance Reduction	Mher Safaryan, Alexandra Peste, Dan Alistarh
40	Add and Thin: Diffusion for Temporal Point Processes	David Lüdke, Marin Biloš, Oleksandr Shchur, Marten Lienen, Stephan Günnemann
41	Exponential Lower Bounds for Fictitious Play in Potential Games	Ioannis Panageas, Nikolas Patris, Stratis Skoulakis, Volkan Cevher
42	No Train No Gain: Revisiting Efficient Training Algorithms For Transformer-based Language Models	Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt Kusner
43	Optimistic Active Exploration of Dynamical Systems	Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause
44	Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts	Emanuele Marconato, Stefano Teso, Antonio Vergari, Andrea Passerini
45	Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data	Boris van Breugel, Nabeel Seedat, Fergus Imrie, Mihaela van der Schaar
46	Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities	Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
47	A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks	Vignesh Kothapalli, Tom Tirer, Joan Bruna
48	Meta-in-context learning in large language models	Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matthew Botvinick, Jane X Wang, Eric Schulz
49	Whatâ€™s Left? Concept Grounding with Logic-Enhanced Foundation Models	Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Jiajun Wu
50	Retrieval-Augmented Multiple Instance Learning	Yufei CUI, Ziquan Liu, Yixin CHEN, Yuchen Lu, Xinyue Yu, Xue Liu, Tei-Wei Kuo, Miguel R. D. Rodrigues, Chun Jason Xue, Antoni B. Chan
51	Soft-Unification in Deep Probabilistic Logic	Jaron Maene, Luc De Raedt
52	Focused Transformer: Contrastive Training for Context Scaling	Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Miłos ́
53	Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off	Zichen Zhang, Johannes Kirschner, Junxi Zhang, Francesco Zanini, Alex Ayoub, Masood Dehghan, Dale Schuurmans
54	False Discovery Proportion control for aggregated Knockoffs	Alexandre Blain, Bertrand Thirion, Olivier Grisel, Pierre Neuvial
55	Swarm Reinforcement Learning for Adaptive Mesh Refinement	Niklas Freymuth, Philipp Dahlinger, Tobias Daniel Würth, Simon Reisch, Luise Kärger, Gerhard Neumann
56	On the impact of activation and normalization in obtaining isometric embeddings at initialization	Amir Joudaki, Hadi Daneshmand, Francis Bach
57	Diffusion Schrödinger Bridge Matching	Yuyang Shi, Valentin De Bortoli, Andrew Campbell, Arnaud Doucet
58	Reinforcement Learning with Simple Sequence Priors	Tankred Saanum, Noemi Elteto, Peter Dayan, Marcel Binz, Eric Schulz
59	Affinity-Aware Graph Networks	Ameya Velingker, Ali Kemal Sinop, Ira Ktena, Petar Veličković, Sreenivas Gollapudi
60	One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning	Marc Rigter, Bruno Lacerda, Nick Hawes
61	Are GATs Out of Balance?	Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz
62	LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas	Kensen Shi, Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
63	Self-Predictive Universal AI	Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Gregoire Deletang, Li Kevin Wenliang, Joel Veness
64	Kernelized Reinforcement Learning with Order Optimal Regret Bounds	Sattar Vakili, Julia Olkhovskaya
65	Recurrent Hypernetworks are Surprisingly Strong in Meta-RL	Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson
66	Principled Weight Initialisation for Input-Convex Neural Networks	Pieter-Jan Hoedt, Günter Klambauer
67	Causal Effect Identification in Uncertain Causal Networks	Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew James Vowels, Jalal Etesami, Negar Kiyavash
68	Latent Space Translation via Semantic Alignment	Valentino Maiorca, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, Emanuele Rodolá
69	Riemannian stochastic optimization methods avoid strict saddle points	Ya-Ping Hsieh, Mohammad Reza Karimi Jaghargh, Andreas Krause, Panayotis Mertikopoulos
70	Successor-Predecessor Intrinsic Exploration	Changmin Yu, Neil Burgess, Maneesh Sahani, Samuel Gershman
71	Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods	Tobit Klug, Dogukan Atik, Reinhard Heckel
72	Particle-based Variational Inference with Generalized Wasserstein Gradient Flow	Ziheng Cheng, Shiyue Zhang, Longlin Yu, Cheng Zhang
73	Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning	Riccardo Zamboni, Alberto Maria Metelli, Marcello Restelli
74	Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data	Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár
75	Identifiability Guarantees for Causal Disentanglement from Soft Interventions	Jiaqi Zhang, Kristjan Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler
76	Active Observing in Continuous-time Control	Samuel Holt, Alihan Hüyük, Mihaela van der Schaar
77	A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models	Alexander Gilbert Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz, Sebastian Weichwald
78	Marginal Density Ratio for Off-Policy Evaluation in Contextual Bandits	Muhammad Faaiz Taufiq, Arnaud Doucet, Rob Cornish, Jean-Francois Ton
79	RegBN: Batch Normalization of Multimodal Data with Regularization	MORTEZA GHAHREMANI, Christian Wachinger
80	Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction	Souhaib Attaiki, Maks Ovsjanikov
81	Differentiable Clustering with Perturbed Spanning Forests	Lawrence Stewart, Francis Bach, Felipe Llinares-López, Quentin Berthet
82	Multiclass Boosting: Simple and Intuitive Weak Learning Criteria	Nataly Brukhim, Amit Daniely, Yishay Mansour, Shay Moran
83	Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts	Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin, Artem Babenko, Liudmila Prokhorenkova
84	PromptRestorer: A Prompting Image Restoration Method with Degradation Perception	Cong Wang, Jinshan Pan, Wei Wang, Jiangxin Dong, Mengzhu Wang, Yakun Ju, Junyang Chen
85	$H$-Consistency Bounds: Characterization and Extensions	Anqi Mao, Mehryar Mohri, Yutao Zhong
86	Contrastive Training of Complex-Valued Autoencoders for Object Discovery	Aleksandar Stanić, Anand Gopalakrishnan, Kazuki Irie, Jürgen Schmidhuber
87	Thinker: Learning to Plan and Act	Stephen Chung, Ivan Anokhin, David Krueger
88	Reliable Off-Policy Learning for Dosage Combinations	Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel
89	Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models	Anant Raj, Umut Simsekli, Alessandro Rudi
90	Beyond Average Return in Markov Decision Processes	Alexandre Marthe, Aurélien Garivier, Claire Vernade
91	(Provable) Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More	Jan Schuchardt, Yan Scholten, Stephan Günnemann
92	Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery	Sarah Rastegar, Hazel Doughty, Cees G. M. Snoek
93	DiffComplete: Diffusion-based Generative 3D Shape Completion	Ruihang Chu, Enze Xie, Shentong Mo, Zhenguo Li, Matthias Nießner, Chi-Wing Fu, Jiaya Jia
94	Spontaneous symmetry breaking in generative diffusion models	Gabriel Raya, Luca Ambrogioni
95	Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards	Alexandre Rame, Guillaume Couairon, Corentin Dancette, Jean-Baptiste Gaya, Mustafa Shukor, Laure Soulier, Matthieu Cord
96	An information-theoretic quantification of the content of communication between brain regions	Marco Celotto, Jan Bím, Alejandro Tlaie, Vito De Feo, Alessandro Toso, Stefan M Lemke, Daniel Chicharro, Hamed Nili, Malte Bieler, Ileana Livia Hanganu-Opatz, Tobias H. Donner, Andrea Brovelli, Stefano Panzeri
97	Adversarial Learning for Feature Shift Detection and Correction	Míriam Barrabés, Daniel Mas Montserrat, Margarita Geleta, Xavier Giró-i-Nieto, Alexander G Ioannidis
98	Normalization Layers Are All That Sharpness-Aware Minimization Needs	Maximilian Mueller, Tiffany Joyce Vlaar, David Rolnick, Matthias Hein
99	Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples	Hao Sun, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
100	Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition	Shuhuai Ren, Aston Zhang, Yi Zhu, Shuai Zhang, Shuai Zheng, Mu Li, Alex Smola, Xu Sun
101	A Fractional Graph Laplacian Approach to Oversmoothing	Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok
102	Point Cloud Completion with Pretrained Text-to-Image Diffusion Models	Yoni Kasten, Ohad Rahamim, Gal Chechik
103	When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability	Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup
104	Limits, approximation and size transferability for GNNs on sparse graphs via graphops	Thien Le, Stefanie Jegelka
105	Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design	Matthew Thomas Jackson, Minqi Jiang, Jack Parker-Holder, Risto Vuorio, Chris Lu, Gregory Farquhar, Shimon Whiteson, Jakob Nicolaus Foerster
106	Improving Language Plasticity via Pretraining with Active Forgetting	Yihong Chen, Kelly Marchisio, Roberta Raileanu, David Ifeoluwa Adelani, Pontus Stenetorp, Sebastian Riedel, Mikel Artetxe
107	D-CIPHER: Discovery of Closed-form Partial Differential Equations	Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
108	Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift	Florian Seligmann, Philipp Becker, Michael Volpp, Gerhard Neumann
109	On Masked Pre-training and the Marginal Likelihood	Pablo Moreno-Muñoz, Pol G. Recasens, Søren Hauberg
110	Maximum Independent Set: Self-Training through Dynamic Programming	Lorenzo Brusca, Lars C.P.M. Quaedvlieg, Stratis Skoulakis, Grigorios Chrysos, Volkan Cevher
111	DELIFFAS: Deformable Light Fields for Fast Avatar Synthesis	YoungJoong Kwon, Lingjie Liu, Henry Fuchs, Marc Habermann, Christian Theobalt
112	Learning To Dive In Branch And Bound	Max B. Paulus, Andreas Krause
113	MultiMoDNâ€”Multimodal, Multi-Task, Interpretable Modular Networks	Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
114	Sharp Bounds for Generalized Causal Sensitivity Analysis	Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel
115	Analyzing Vision Transformers for Image Classification in Class Embedding Space	Martina G. Vilas, Timothy Schaumlöffel, Gemma Roig
116	$p$-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison	Kai Klede, Thomas Altstidl, Dario Zanca, Bjoern Eskofier
117	Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training	Aleksandra Nowak, Bram Grooten, Decebal Constantin Mocanu, Jacek Tabor
118	Taylor TD-learning	Michele Garibbo, Maxime Robeyns, Laurence Aitchison
119	Use perturbations when learning from explanations	Juyeon Heo, Vihari Piratla, Matthew Robert Wicker, Adrian Weller
120	Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration	Longlin Yu, Tianyu Xie, Yu Zhu, Tong Yang, Xiangyu Zhang, Cheng Zhang
121	How do Minimum-Norm Shallow Denoisers Look in Function Space?	Chen Zeno, Greg Ongie, Yaniv Blumenfeld, Nir Weinberger, Daniel Soudry
122	Finding Safe Zones of Markov Decision Processes Policies	Lee Cohen, Yishay Mansour, Michal Moshkovitz
123	Learning Provably Robust Estimators for Inverse Problems via Jittering	Anselm Krainovic, Mahdi Soltanolkotabi, Reinhard Heckel
124	Partial Matrix Completion	Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun
125	Labeling Neural Representations with Inverse Recognition	Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina MC Höhne
126	Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective	Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S Kevin Zhou, Lawrence Hamilton Staib, James s Duncan
127	Incentivizing Honesty among Competitors in Collaborative Learning and Optimization	Florian E. Dorner, Nikola Konstantinov, Georgi Stoyanov Pashaliev, Martin Vechev
128	LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer	Haoyu Chen, Hao Tang, Radu Timofte, Luc Van Gool, Guoying Zhao
129	Neural (Tangent Kernel) Collapse	Mariia Seleznova, Dana Weitzner, Raja Giryes, Gitta Kutyniok, Hung-Hsu Chou
130	Meek Separators and Their Applications in Targeted Causal Discovery	Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler
131	Permutation Equivariant Neural Functionals	Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J Zico Kolter, Chelsea Finn
132	Two Sides of One Coin: the Limits of Untuned SGD and the Power of Adaptive Methods	Junchi YANG, Xiang Li, Ilyas Fatkhullin, Niao He
133	Norm-guided latent space exploration for text-to-image generation	Dvir Samuel, Rami Ben-Ari, Nir Darshan, Haggai Maron, Gal Chechik
134	Black-Box Differential Privacy for Interactive ML	Haim Kaplan, Yishay Mansour, Shay Moran, Kobbi Nissim, Uri Stemmer
135	LaFTer: Label-Free Tuning of Zero-shot Classifier using Language and Unlabeled Image Collections	Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Horst Possegger, Mateusz Kozinski, Rogerio Feris, Horst Bischof
136	Resilient Multiple Choice Learning: A learned scoring scheme with application to audio scene analysis	Victor Letzelter, Mathieu Fontaine, Mickael Chen, Patrick Perez, Slim Essid, Gaël Richard
137	Semantic HELM: A Human-Readable Memory for Reinforcement Learning	Fabian Paischer, Thomas Adler, Markus Hofmarcher, Sepp Hochreiter
138	Penguin: Parallel-Packed Homomorphic Encryption for Fast Graph Convolutional Network Inference	Ran Ran, Nuo Xu, Tao Liu, Wei Wang, Gang Quan, Wujie Wen
139	TRIAGE: Characterizing and auditing training data for improved regression	Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar
140	POP-3D: Open-Vocabulary 3D Occupancy Prediction from Images	Antonín Vobecký, Oriane Siméoni, David Hurych, Spyros Gidaris, Andrei Bursuc, Patrick Perez, Josef Sivic
141	CLadder: A Benchmark to Assess Causal Reasoning Capabilities of Language Models	Zhijing Jin, Yuen Chen, Felix Leeb, Luigi Gresele, Ojasv Kamal, Zhiheng LYU, Kevin Blin, Fernando Gonzalez Adauto, Max Kleiman-Weiner, Mrinmaya Sachan, Bernhard Schölkopf
142	GMSF: Global Matching Scene Flow	Yushan Zhang, Johan Edstedt, Bastian Wandt, Per-Erik Forssen, Maria Magnusson, Michael Felsberg
143	Compositional Foundation Models for Hierarchical Planning	Anurag Ajay, Seungwook Han, Yilun Du, Shuang Li, Abhi Gupta, Tommi S. Jaakkola, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Akash Srivastava, Pulkit Agrawal
144	The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions	Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp
145	Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery	Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłos ́
146	Deep Gaussian Markov Random Fields for Graph-Structured Dynamical Systems	Fiona Lippert, Bart Kranstauber, E. Emiel van Loon, Patrick Forré
147	Self-Correcting Bayesian Optimization through Bayesian Active Learning	Carl Hvarfner, Erik Orm Hellsten, Frank Hutter, Luigi Nardi
148	ZipLM: Inference-Aware Structured Pruning of Language Models	Eldar Kurtic, Elias Frantar, Dan Alistarh
149	How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization	Hai Zhang, Hang Yu, Junqiao Zhao, Di Zhang, Chang Huang, Hongtu Zhou, Xiao Zhang, Chen Ye
150	Zero-Shot Anomaly Detection via Batch Normalization	Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
151	Implicit Manifold Gaussian Process Regression	Bernardo Fichera, Viacheslav Borovitskiy, Andreas Krause, Aude Billard
152	A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference	Emile van Krieken, Thiviyan Thanapalasingam, Jakub M. Tomczak, Frank Van Harmelen, Annette Ten Teije
153	Estimating the Rate-Distortion Function by Wasserstein Gradient Descent	Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt
154	Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning	Fan Feng, Sara Magliacane
155	EDGI: Equivariant Diffusion for Planning with Embodied Agents	Johann Brehmer, Joey Bose, Pim De Haan, Taco Cohen
156	Lie Point Symmetry and Physics-Informed Networks	Tara Akhound-Sadegh, Laurence Perreault-Levasseur, Johannes Brandstetter, Max Welling, Siamak Ravanbakhsh
157	Kissing to Find a Match: Efficient Low-Rank Permutation Representation	Hannah Dröge, Zorah Lähner, Yuval Bahat, Onofre Martorell Nadal, Felix Heide, Michael Moeller
158	Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation	Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan Suykens
159	Riemannian Laplace approximations for Bayesian neural networks	Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
160	Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack	Pratik Karmakar, Debabrota Basu
161	On the Ability of Graph Neural Networks to Model Interactions Between Vertices	Noam Razin, Tom Verbin, Nadav Cohen
162	LEACE: Perfect linear concept erasure in closed form	Nora Belrose, David Schneider-Joseph, Shauli Ravfogel, Ryan Cotterell, Edward Raff, Stella Biderman
163	Risk-Averse Active Sensing for Timely Outcome Prediction under Cost Pressure	Yuchao Qin, Mihaela van der Schaar, Changhee Lee
164	MarioGPT: Open-Ended Text2Level Generation through Large Language Models	Shyam Sudhakaran, Miguel González-Duque, Matthias Freiberger, Claire Glanois, Elias Najarro, Sebastian Risi
165	Anchor Data Augmentation	Nora Schneider, Shirin Goshtasbpour, Fernando Perez-Cruz
166	Learning to Modulate pre-trained Models in RL	Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter
167	Training Chain-of-Thought via Latent-Variable Inference	Du Phan, Matthew Douglas Hoffman, david dohan, Sholto Douglas, Tuan Anh Le, Aaron T Parisi, Pavel Sountsov, Charles Sutton, Sharad Vikram, Rif A. Saurous
168	SE(3) Diffusion Model-based Point Cloud Registration for Robust 6D Object Pose Estimation	Haobo Jiang, Mathieu Salzmann, Zheng Dang, Jin Xie, Jian Yang
169	Optimistic Meta-Gradients	Sebastian Flennerhag, Tom Zahavy, Brendan O'Donoghue, Hado van Hasselt, András György, Satinder Singh
170	A Definition of Continual Reinforcement Learning	David Abel, Andre Barreto, Benjamin Van Roy, Doina Precup, Hado van Hasselt, Satinder Singh
171	On kernel-based statistical learning theory in the mean field limit	Christian Fiedler, Michael Herty, Sebastian Trimpe
172	Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images	Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
173	Anytime Model Selection in Linear Bandits	Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano
174	Autodecoding Latent 3D Diffusion Models	Evangelos Ntavelis, Aliaksandr Siarohin, Kyle Olszewski, Chaoyang Wang, Luc Van Gool, Sergey Tulyakov
175	Real-Time Motion Prediction via Heterogeneous Polyline Transformer with Relative Pose Encoding	Zhejun Zhang, Alexander Liniger, Christos Sakaridis, Fisher Yu, Luc Van Gool
176	BiMatting: Efficient Video Matting via Binarization	Haotong Qin, Lei Ke, Xudong Ma, Martin Danelljan, Yu-Wing Tai, Chi-Keung Tang, Xianglong Liu, Fisher Yu
177	Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities	Jingyuan Sun, Mingxiao Li, Zijiao Chen, Yunhao Zhang, Shaonan Wang, Marie-Francine Moens
178	Structured Prediction with Stronger Consistency Guarantees	Anqi Mao, Mehryar Mohri, Yutao Zhong
179	$\textbf{A}^2\textbf{CiD}^2$: Accelerating Asynchronous Communication in Decentralized Deep Learning	Adel Nabli, Eugene Belilovsky, Edouard Oyallon
180	Finding Counterfactually Optimal Action Sequences in Continuous State Spaces	Stratis Tsirtsis, Manuel Gomez Rodriguez
181	CAP: Correlation-Aware Pruning for Highly-Accurate Sparse Vision Models	Denis Kuznedelev, Eldar Kurtic, Elias Frantar, Dan Alistarh
182	ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training	Antonio Norelli, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, Francesco Locatello
183	A Bayesian Approach To Analysing Training Data Attribution In Deep Learning	Elisa Nguyen, Minjoon Seo, Seong Joon Oh
184	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise	Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
185	Stochastic Approximation Algorithms for Systems of Interacting Particles	Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
186	Latent SDEs on Homogeneous Spaces	Sebastian Zeng, Florian Graf, Roland Kwitt
187	Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex	Drew Linsley, Ivan F Rodriguez Rodriguez, Thomas FEL, Michael Arcaro, Saloni Sharma, Margaret Livingstone, Thomas Serre
188	Causal Imitability Under Context-Specific Independence Relations	Fateme Jamshidi, Sina Akbari, Negar Kiyavash
189	Probabilistic Invariant Learning with Randomized Linear Classifiers	Leonardo Cotta, Gal Yehuda, Assaf Schuster, Chris J. Maddison
190	Joint Training of Deep Ensembles Fails Due to Learner Collusion	Alan Jeffares, Tennison Liu, Jonathan Crabbé, Mihaela van der Schaar
191	Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models	Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl
192	Multiplication-Free Transformer Training via Piecewise Affine Operations	Atli Kosson, Martin Jaggi
193	Patch nâ€™ Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution	Mostafa Dehghani, Basil Mustafa, Josip Djolonga, Jonathan Heek, Matthias Minderer, Mathilde Caron, Andreas Peter Steiner, Joan Puigcerver, Robert Geirhos, Ibrahim Alabdulmohsin, Avital Oliver, Piotr Padlewski, Alexey A. Gritsenko, Mario Lucic, Neil Houlsby
194	Efficient Exploration in Continuous-time Model-based Reinforcement Learning	Lenart Treven, Jonas Hübotter, Bhavya Sukhija, Florian Dorfler, Andreas Krause
195	RDumb: A simple approach that questions our progress in continual test-time adaptation	Ori Press, Steffen Schneider, Matthias Kuemmerer, Matthias Bethge
196	Score-based Data Assimilation	François Rozet, Gilles Louppe
197	Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery	Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
198	Regret Minimization via Saddle Point Optimization	Johannes Kirschner, Alireza Bakhtiari, Kushagra Chandak, Volodymyr Tkachuk, Csaba Szepesvari
199	Nonparametric Identifiability of Causal Representations from Unknown Interventions	Julius von Kügelgen, Michel Besserve, Wendong Liang, Luigi Gresele, Armin Kekić, Elias Bareinboim, David Blei, Bernhard Schölkopf
200	Textually Pretrained Speech Language Models	Michael Hassid, Tal Remez, Tu Anh Nguyen, Itai Gat, Alexis Conneau, Felix Kreuk, Jade Copet, Alexandre Défossez, Gabriel Synnaeve, Emmanuel Dupoux, Roy Schwartz, Yossi Adi
201	Learning to Tokenize for Generative Retrieval	Weiwei Sun, Lingyong Yan, Zheng Chen, Shuaiqiang Wang, Haichao Zhu, Pengjie Ren, Zhumin Chen, Dawei Yin, Maarten de Rijke, Zhaochun Ren
202	Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention	Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret
203	Attacks on Online Learners: a Teacher-Student Analysis	Riccardo Giuseppe Margiotta, Sebastian Goldt, Guido Sanguinetti
204	Learning Rate Free Bayesian Inference in Constrained Domains	Louis Sharrock, Lester Mackey, Christopher Nemeth
205	REx: Data-Free Residual Quantization Error Expansion	Edouard YVINEC, Arnaud Dapogny, Matthieu Cord, Kevin Bailly
206	Connecting Certified and Adversarial Training	Yuhao Mao, Mark Niklas Mueller, Marc Fischer, Martin Vechev
207	Persuading Farsighted Receivers in MDPs: the Power of Honesty	Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti
208	An Optimal Structured Zeroth-order Algorithm for Non-smooth Optimization	Marco Rando, Cesare Molinari, Lorenzo Rosasco, Silvia Villa
209	DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation	Shentong Mo, Enze Xie, Ruihang Chu, Lanqing HONG, Matthias Nießner, Zhenguo Li
210	Learning Robust Statistics for Simulation-based Inference under Model Misspecification	Daolang Huang, Ayush Bharti, Amauri H Souza, Luigi Acerbi, Samuel Kaski
211	Cognitive Model Discovery via Disentangled RNNs	Kevin J Miller, Maria K Eckstein, Matthew Botvinick, Zeb Kurth-Nelson
212	Variational Annealing on Graphs for Combinatorial Optimization	Sebastian Sanokowski, Wilhelm Franz Berghammer, Sepp Hochreiter, Sebastian Lehner
213	Contextual Stochastic Bilevel Optimization	Yifan Hu, Jie Wang, Yao Xie, Andreas Krause, Daniel Kuhn
214	Collaborative Learning via Prediction Consensus	Dongyang Fan, Celestine Mendler-Dünner, Martin Jaggi
215	Transportability for Bandits with Data from Different Environments	Alexis Bellot, Alan Malek, Silvia Chiappa
216	Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel	Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamas Sarlos, Adrian Weller
217	On Imitation in Mean-field Games	Giorgia Ramponi, Pavel Kolev, Olivier Pietquin, Niao He, Mathieu Lauriere, Matthieu Geist
218	Segment Anything in High Quality	Lei Ke, Mingqiao Ye, Martin Danelljan, Yifan liu, Yu-Wing Tai, Chi-Keung Tang, Fisher Yu
219	Scaling MLPs: A Tale of Inductive Bias	Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann
220	Advice Querying under Budget Constraint for Online Algorithms	Ziyad Benomar, Vianney Perchet
221	Goal-conditioned Offline Planning from Curious Exploration	Marco Bagatella, Georg Martius
222	CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning	Charles Guille-Escuret, Pau Rodriguez, David Vazquez, Ioannis Mitliagkas, Joao Monteiro
223	Lossy Image Compression with Conditional Diffusion Models	Ruihan Yang, Stephan Mandt
224	Does Visual Pretraining Help End-to-End Reasoning?	Chen Sun, Calvin Luo, Xingyi Zhou, Anurag Arnab, Cordelia Schmid
225	The Shaped Transformer: Attention Models in the Infinite Depth-and-Width Limit	Lorenzo Noci, Chuning Li, Mufan Bill Li, Bobby He, Thomas Hofmann, Chris J. Maddison, Daniel M. Roy
226	Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach	Riccardo Poiani, Nicole Nobili, Alberto Maria Metelli, Marcello Restelli
227	Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models	Naman Deep Singh, Francesco Croce, Matthias Hein
228	Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction	Quentin Delfosse, Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
229	Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback	Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter
230	Universality laws for Gaussian mixtures in generalized linear models	Yatin Dandi, Ludovic Stephan, Florent Krzakala, Bruno Loureiro, Lenka Zdeborova
231	ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation	Björn Deiseroth, Mayukh Deb, Samuel Weinbach, Manuel Brack, Patrick Schramowski, Kristian Kersting
232	Weakly Supervised 3D Open-vocabulary Segmentation	Kunhao Liu, Fangneng Zhan, Jiahui Zhang, MUYU XU, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric Xing, Shijian Lu
233	Modulated Neural ODEs	Ilze Amanda Auzina, Cagatay Yildiz, Sara Magliacane, Matthias Bethge, Efstratios Gavves
234	On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence	Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu
235	Human spatiotemporal pattern learning as probabilistic program synthesis	Tracey Mills, Joshua B. Tenenbaum, Samuel J Cheyette
236	Geometric Neural Diffusion Processes	Emile Mathieu, Vincent Dutordoir, Michael John Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E Turner
237	Moment Matching Denoising Gibbs Sampling	Mingtian Zhang, Alex Hawkins-Hooker, Brooks Paige, David Barber
238	First- and Second-Order Bounds for Adversarial Linear Contextual Bandits	Julia Olkhovskaya, Jack Mayo, Tim van Erven, Gergely Neu, Chen-Yu Wei
239	To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning	Ildus Sadrtdinov, Dmitrii Pozdeev, Dmitry P. Vetrov, Ekaterina Lobacheva
240	Policy Gradient for Rectangular Robust Markov Decision Processes	Navdeep Kumar, Esther Derman, Matthieu Geist, Kfir Yehuda Levy, Shie Mannor
241	Monte Carlo Tree Search with Boltzmann Exploration	Michael Painter, Mohamed Baioumy, Nick Hawes, Bruno Lacerda
242	Online Learning under Adversarial Nonlinear Constraints	Pavel Kolev, Georg Martius, Michael Muehlebach
243	Understanding and Improving Ensemble Adversarial Defense	Yian Deng, Tingting Mu
244	Active Learning-Based Species Range Estimation	Christian Lange, Elijah Cole, Grant Van Horn, Oisin Mac Aodha
245	Tanimoto Random Features for Scalable Molecular Machine Learning	Austin Tripp, Sergio Bacallado, Sukriti Singh, José Miguel Hernández-Lobato
246	Should Under-parameterized Student Networks Copy or Average Teacher Weights?	Berfin Simsek, Amire Bendjeddou, Wulfram Gerstner, Johanni Brea
247	Geometric Algebra Transformer	Johann Brehmer, Pim De Haan, Sönke Behrends, Taco Cohen
248	Transformers learn to implement preconditioned gradient descent for in-context learning	Kwangjun Ahn, Xiang Cheng, Hadi Daneshmand, Suvrit Sra
249	Diffused Redundancy in Pre-trained Representations	Vedant Nanda, Till Speicher, John P Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller
250	Compositional Generalization from First Principles	Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel
251	Flow Factorized Representation Learning	Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling
252	Individualized Dosing Dynamics via Neural Eigen Decomposition	Stav Belogolovsky, Ido Greenberg, Danny Eytan, Shie Mannor
253	What functions can Graph Neural Networks compute on random graphs? The role of Positional Encoding	Nicolas Keriven, Samuel Vaiter
254	Deep Stochastic Processes via Functional Markov Transition Operators	Jin Xu, Emilien Dupont, Kaspar Märtens, Tom Rainforth, Yee Whye Teh
255	Stochastic Optimal Control for Collective Variable Free Sampling of Molecular Transition Paths	Lars Holdijk, Yuanqi Du, Ferry Hooft, Priyank Jaini, Bernd Ensing, Max Welling
256	Disentanglement via Latent Quantization	Kyle Hsu, Will Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn
257	SNAP: Self-Supervised Neural Maps for Visual Positioning and Semantic Understanding	Paul-Edouard Sarlin, Eduard Trulls, Marc Pollefeys, Jan Hosang, Simon Lynen
258	Trial matching: capturing variability with data-constrained spiking neural networks	Christos Sourmpis, Carl C. H. Petersen, Wulfram Gerstner, Guillaume Bellec
259	Latent Field Discovery in Interacting Dynamical Systems with Neural Fields	Miltiadis Kofinas, Erik J Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
260	Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings	Klim Kireev, Maksym Andriushchenko, Carmela Troncoso, Nicolas Flammarion
261	Prediction and Control in Continual Reinforcement Learning	Nishanth Anand, Doina Precup
262	Faster Relative Entropy Coding with Greedy Rejection Coding	Gergely Flamich, Stratis Markou, José Miguel Hernández-Lobato
263	Trading-off price for data quality to achieve fair online allocation	Mathieu Molina, Nicolas Gast, Patrick Loiseau, Vianney Perchet
264	Conformal Prediction for Time Series with Modern Hopfield Networks	Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter
265	Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation	Giorgio Giannone, Akash Srivastava, Ole Winther, Faez Ahmed
266	First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities	Aleksandr Beznosikov, Sergey Samsonov, Marina Sheshukova, Alexander Gasnikov, Alexey Naumov, Eric Moulines
267	SEGA: Instructing Text-to-Image Models using Semantic Guidance	Manuel Brack, Felix Friedrich, Dominik Hintersdorf, Lukas Struppek, Patrick Schramowski, Kristian Kersting
268	LIMA: Less Is More for Alignment	Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, LILI YU, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy
269	DropCompute: simple and more robust distributed synchronous training via compute variance reduction	Niv Giladi, Shahar Gottlieb, Moran Shkolnik, Asaf Karnieli, Ron Banner, Elad Hoffer, Kfir Yehuda Levy, Daniel Soudry
270	Controlling Text-to-Image Diffusion by Orthogonal Finetuning	Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf
271	Train Hard, Fight Easy: Robust Meta Reinforcement Learning	Ido Greenberg, Shie Mannor, Gal Chechik, Eli Meirom
272	Penalising the biases in norm regularisation enforces sparsity	Etienne Boursier, Nicolas Flammarion
273	Neural Functional Transformers	Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J Zico Kolter, Chelsea Finn
274	Vocabulary-free Image Classification	Alessandro Conti, Enrico Fini, Massimiliano Mancini, Paolo Rota, Yiming Wang, Elisa Ricci
275	Simple, Scalable and Effective Clustering via One-Dimensional Projections	Moses Charikar, Monika Henzinger, Lunjia Hu, Maximilian Vötsch, Erik Waingarten
276	Make Pre-trained Model Reversible: From Parameter to Memory Efficient Fine-Tuning	Baohao Liao, Shaomu Tan, Christof Monz
277	Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization	Thomas FEL, Thibaut Boissin, Victor Boutin, Agustin Martin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom ROUSSEAU, Remi Cadene, Lore Goetschalckx, Laurent Gardes, Thomas Serre
278	Assumption violations in causal discovery and the robustness of score matching	Francesco Montagna, Atalanti A. Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, Francesco Locatello
279	Model-free Posterior Sampling via Learning Rate Randomization	Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, pierre perrault, Michal Valko, Pierre MENARD
280	Why Did This Model Forecast This Future? Information-Theoretic Saliency for Counterfactual Explanations of Probabilistic Regression Models	Chirag Raman, Alec Nonnemaker, Amelia Villegas-Morcillo, Hayley Hung, Marco Loog
281	Intriguing Properties of Quantization at Scale	Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Zhen Stephen Gou, Phil Blunsom, Ahmet Ãœstün, Sara Hooker
282	Optimization or Architecture: How to Hack Kalman Filtering	Ido Greenberg, Netanel Yannay, Shie Mannor
283	Towards Characterizing the First-order Query Complexity of Learning (Approximate) Nash Equilibria in Zero-sum Matrix Games	Hedi Hadiji, Sarah Sachs, Tim van Erven, Wouter M Koolen
284	Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks	Jiayuan Ye, Zhenyu Zhu, Fanghui Liu, Reza Shokri, Volkan Cevher
285	SHAP-IQ: Unified Approximation of any-order Shapley Interactions	Fabian Fumagalli, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier, Barbara Eva Hammer
286	Understanding and Mitigating Copying in Diffusion Models	Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
287	Causal Component Analysis	Wendong Liang, Armin Kekić, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
288	Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammars	Simon Schrodi, Danny Stoll, Binxin Ru, Rhea Sanjay Sukthanker, Thomas Brox, Frank Hutter
289	Guiding The Last Layer in Federated Learning with Pre-Trained Models	Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky
290	Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples	Shashanka Venkataramanan, Ewa Kijak, Laurent Amsaleg, Yannis Avrithis
291	Robust covariance estimation with missing values and cell-wise contamination	Gregoire Pacreau, Karim Lounici
292	Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning	Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause
293	Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization	Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales López, Ingmar Posner, Xiaowen Dong
294	Human-Aligned Calibration for AI-Assisted Decision Making	Nina L. Corvelo Benz, Manuel Gomez Rodriguez
295	Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning	Mitsuhiko Nakamoto, Yuexiang Zhai, Anikait Singh, Max Sobol Mark, Yi Ma, Chelsea Finn, Aviral Kumar, Sergey Levine
296	Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions	Lukas Gosch, Simon Geisler, Daniel Sturm, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
297	Estimating Koopman operators with sketching to provably learn large scale dynamical systems	Giacomo Meanti, Antoine Chatalic, Vladimir R Kostic, Pietro Novelli, massimiliano pontil, Lorenzo Rosasco
298	Two-Stage Learning to Defer with Multiple Experts	Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong
299	High dimensional, tabular deep learning with an auxiliary knowledge graph	Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec
300	CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion	Anders Vestergaard Nørskov, Alexander Neergaard Zahid, Morten Mørup
301	Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation	Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy
302	Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives	Tom Monnier, Jake Austin, Angjoo Kanazawa, Alexei A Efros, Mathieu Aubry
303	3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes	Haotian Xue, Antonio Torralba, Joshua B. Tenenbaum, Daniel LK Yamins, Yunzhu Li, Hsiao-Yu Tung
304	FedL2P: Federated Learning to Personalize	Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy Hospedales, Ferenc Huszár, Nicholas Donald Lane
305	Pseudo-Likelihood Inference	Theo Gruner, Boris Belousov, Fabio Muratore, Daniel Palenicek, Jan Peters
306	On the spectral bias of two-layer linear networks	Aditya Vardhan Varre, Maria-Luiza Vladarean, Loucas Pillaud-Vivien, Nicolas Flammarion
307	Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective	João B. S. Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, Joachim M. Buhmann
308	RRHF: Rank Responses to Align Language Models with Human Feedback	Hongyi Yuan, Zheng Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, Fei Huang
309	Context-lumpable stochastic bandits	Chung-Wei Lee, Qinghua Liu, Yasin Abbasi-Yadkori, Chi Jin, Tor Lattimore, Csaba Szepesvari
310	Reward Imputation with Sketching for Contextual Batched Bandits	Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen
311	Curvature Filtrations for Graph Generative Model Evaluation	Joshua Southern, Jeremy Wayland, Michael M. Bronstein, Bastian Rieck
312	Statistically Valid Variable Importance Assessment through Conditional Permutations	Ahmad Chamma, Denis Engemann, Bertrand Thirion
313	RoboCLIP: One Demonstration is Enough to Learn Robot Policies	Sumedh Anand Sontakke, Jesse Zhang, Séb Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti
314	Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes	Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
315	Flow Matching for Scalable Simulation-Based Inference	Jonas Bernhard Wildberger, Maximilian Dax, Simon Buchholz, Stephen R Green, Jakob H. Macke, Bernhard Schölkopf
316	Online POMDP Planning with Anytime Deterministic Guarantees	Moran Barenboim, Vadim Indelman
317	Convolution Monge Mapping Normalization for learning on sleep data	Theo Gnassounou, Rémi Flamary, Alexandre Gramfort
318	When Visual Prompt Tuning Meets Source-Free Domain Adaptive Semantic Segmentation	Xinhong Ma, Yiming Wang, Hao Liu, Tianyu Guo, Yunhe Wang
319	Smooth, exact rotational symmetrization for deep learning on point clouds	Sergey Pozdnyakov, Michele Ceriotti
320	Spuriosity Didn't Kill the Classifier: Using Invariant Predictions to Harness Spurious Features	Cian Eastwood, Shashank Singh, Andrei Liviu Nicolicioiu, Marin Vlastelica, Julius von Kügelgen, Bernhard Schölkopf
321	Koopman Kernel Regression	Petar Bevanda, Max Beier, Armin Lederer, Stefan Georg Sosnowski, Eyke Hüllermeier, Sandra Hirche
322	Regularity as Intrinsic Reward for Free Play	Cansu Sancaktar, Justus Piater, Georg Martius
323	ProteinNPT: Improving protein property prediction and design with non-parametric transformers	Pascal Notin, Ruben Weitzman, Debora Susan Marks, Yarin Gal
324	FeCAM: Exploiting the Heterogeneity of Class Distributions in Exemplar-Free Continual Learning	Dipam Goswami, Yuyang Liu, BartÅ‚omiej Twardowski, Joost van de Weijer
325	Towards Anytime Classification in Early-Exit Architectures by Enforcing Conditional Monotonicity	Metod Jazbec, James Urquhart Allingham, Dan Zhang, Eric Nalisnick
326	Strategic Data Sharing between Competitors	Nikita Tsoy, Nikola Konstantinov
327	MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation	Marco Bellagente, Manuel Brack, Hannah Benita Teufel, Felix Friedrich, Björn Deiseroth, Constantin Eichenberg, Andrew Dai, Robert John Nicholas Baldock, Souradeep Nanda, Koen Oostermeijer, Andres Felipe Cruz-Salinas, Patrick Schramowski, Kristian Kersting, Samuel Weinbach
328	Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation	Yun Xing, Jian Kang, Aoran Xiao, Jiahao Nie, Ling Shao, Shijian Lu
329	Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering	Noah Hollmann, Samuel Müller, Frank Hutter
330	Intervention Generalization: A View from Factor Graph Models	Gecia Bravo-Hermsdorff, David Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva
331	Test-time Training for Matching-based Video Object Segmentation	Juliette Bertrand, Giorgos Kordopatis-Zilos, Yannis Kalantidis, Giorgos Tolias
332	Accelerating Motion Planning via Optimal Transport	An Thai Le, Georgia Chalvatzaki, Armin Biess, Jan Peters
333	OpenMask3D: Open-Vocabulary 3D Instance Segmentation	Ayça Takmaz, Elisabetta Fedele, Robert Sumner, Marc Pollefeys, Federico Tombari, Francis Engelmann
334	Provably Efficient Offline Reinforcement Learning in Regular Decision Processes	Roberto Cipollone, Anders Jonsson, Alessandro Ronca, Mohammad Sadegh Talebi
335	On the Convergence of Encoder-only Shallow Transformers	Yongtao Wu, Fanghui Liu, Grigorios Chrysos, Volkan Cevher
336	MeGraph: Capturing Long-Range Interactions by Alternating Local and Hierarchical Aggregation on Multi-Scaled Graph Hierarchy	Honghua Dong, Jiawei Xu, Yu Yang, Rui Zhao, Shiwen Wu, Chun Yuan, Xiu Li, Chris J. Maddison, Lei Han
337	Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects	Tianhang Cheng, Wei-Chiu Ma, Kaiyu Guan, Antonio Torralba, Shenlong Wang
338	Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills	Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Xiling Li, Rudolf Lioutikov, Gerhard Neumann
339	Random-Access Infinite Context Length for Transformers	Amirkeivan Mohtashami, Martin Jaggi
340	Certification of Distributional Individual Fairness	Matthew Robert Wicker, Vihari Piratla, Adrian Weller
341	Joint processing of linguistic properties in brains and language models	SUBBA REDDY OOTA, Manish Gupta, Mariya Toneva
342	A State Representation for Diminishing Rewards	Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana L Borsa, Maneesh Sahani
343	Bounding training data reconstruction in DP-SGD	Jamie Hayes, Borja Balle, Saeed Mahloujifar
344	AVIS: Autonomous Visual Information Seeking with Large Language Model Agent	Ziniu Hu, Ahmet Iscen, Chen Sun, Kai-Wei Chang, Yizhou Sun, David A Ross, Cordelia Schmid, Alireza Fathi
345	Language Model Tokenizers Introduce Unfairness Between Languages	Aleksandar Petrov, Emanuele La Malfa, Philip Torr, Adel Bibi
346	Synthetic Experience Replay	Cong Lu, Philip J. Ball, Yee Whye Teh, Jack Parker-Holder
347	Hierarchical Randomized Smoothing	Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann
348	DDF-HO: Hand-Held Object Reconstruction via Conditional Directed Distance Field	Chenyangguang Zhang, Yan Di, Ruida Zhang, Guangyao Zhai, Fabian Manhardt, Federico Tombari, Xiangyang Ji
349	No Representation Rules Them All in Category Discovery	Sagar Vaze, Andrea Vedaldi, Andrew Zisserman
350	Quantification of Uncertainty with Adversarial Models	Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter
351	Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance	Jonathan Crabbé, Mihaela van der Schaar
352	Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing	Kai Wang, Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost van de Weijer
353	Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval	Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg
354	Likelihood Ratio Confidence Sets for Sequential Decision Making	Nicolas Emmenegger, Mojmir Mutny, Andreas Krause
355	Learning Sample Difficulty from Pre-trained Models for Reliable Prediction	Peng Cui, Dan Zhang, Zhijie Deng, Yinpeng Dong, Jun Zhu
356	Adaptive Selective Sampling for Online Prediction with Experts	Rui M. Castro, Fredrik Hellström, Tim van Erven
357	Binary Classification with Confidence Difference	Wei Wang, Lei Feng, Yuchen Jiang, Gang Niu, Min-Ling Zhang, Masashi Sugiyama
358	High Precision Causal Model Evaluation with Conditional Randomization	Chao Ma, Cheng Zhang
359	On the Exploitability of Instruction Tuning	Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
360	Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation	Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler
361	A Unified Framework for U-Net Design and Analysis	Christopher Williams, Fabian Falck, George Deligiannidis, Christopher C. Holmes, Arnaud Doucet, Saifuddin Syed
362	Learning Large Graph Property Prediction via Graph Segment Training	Kaidi Cao, Phitchaya Mangpo Phothilimthana, Sami Abu-El-Haija, Dustin Zelle, Yanqi Zhou, Charith Mendis, Jure Leskovec, Bryan Perozzi
363	Learning via Wasserstein-Based High Probability Generalisation Bounds	Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
364	Explore to Generalize in Zero-Shot RL	Ev Zisselman, Itai Lavie, Daniel Soudry, Aviv Tamar
365	What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models	Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang
366	Probabilistic Exponential Integrators	Nathanael Bosch, Philipp Hennig, Filip Tronarp
367	Group Robust Classification Without Any Group Information	Christos Tsirigotis, Joao Monteiro, Pau Rodriguez, David Vazquez, Aaron Courville
368	ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns	Ren Li, Benoît Guillard, Pascal Fua
369	Sharpness-Aware Minimization Leads to Low-Rank Features	Maksym Andriushchenko, Dara Bahri, Hossein Mobahi, Nicolas Flammarion
370	Beyond Normal: On the Evaluation of Mutual Information Estimators	Paweł Czyż, Frederic Grabowski, Julia E Vogt, Niko Beerenwinkel, Alexander Marx
371	Topological Obstructions and How to Avoid Them	Babak Esmaeili, Robin Walters, Heiko Zimmermann, Jan-Willem van de Meent
372	Implicit Transfer Operator Learning: Multiple Time-Resolution Models for Molecular Dynamics	Mathias Schreiner, Ole Winther, Simon Olsson
373	Learning Unseen Modality Interaction	Yunhua Zhang, Hazel Doughty, Cees G. M. Snoek
374	Robust Knowledge Transfer in Tiered Reinforcement Learning	Jiawei Huang, Niao He
375	CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graphs	Guangyao Zhai, Evin Pinar Örnek, Shun-Cheng Wu, Yan Di, Federico Tombari, Nassir Navab, Benjamin Busam
376	Adapting Neural Link Predictors for Data-Efficient Complex Query Answering	Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein
377	Practical differentially private hyperparameter tuning with subsampling	Antti Koskela, Tejas Kulkarni
378	Improving the privacy and practicality of objective pertubation for differentially private linear learners	Rachel Redberg, Antti Koskela, Yu-Xiang Wang
379	Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels.	Wang, Z., X. Ning, M. B. Blaschko
380	Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union.	Wang, Z., M. Berman, A. Rannen-Triki, P. Torr, D. Tuia, T. Tuytelaars, L. Van Gool, J. Yu, M. B. Blaschko
381	Learning to Learn Prototypical Networks by Task-Guided Diffusion	Yingjun Du, Zehao Xiao, Shencai Liao, Cees Snoek
382	Conditional Mutual Information for Disentangled Representations in Reinfordement Learning	Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck, Josiah P. Hanna, Stefano V. Albrecht

NeurIPS 2023 spotlight

#	Paper Title	List of authors (ELLIS members in bold)
1	Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL	Qinghua Liu, Gellért Weisz, András György, Chi Jin, Csaba Szepesvari
2	Unpaired Multi-Domain Causal Representation Learning	Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler
3	Quasi-Monte Carlo Graph Random Features	Isaac Reid, Adrian Weller, Krzysztof Marcin Choromanski
4	Uncertainty Quantification over Graph with Conformalized Graph Neural Networks	Kexin Huang, Ying Jin, Emmanuel Candes, Jure Leskovec
5	Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency	Owen Queen, Thomas Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik
6	The Geometry of Neural Nets' Parameter Spaces Under Reparametrization	Agustinus Kristiadi, Felix Dangel, Philipp Hennig
7	Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model	Peter Súkeník, Marco Mondelli, Christoph H Lampert
8	Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers	Sotiris Anagnostidis, Dario Pavllo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann
9	Can semi-supervised learning use all the data effectively? A lower bound perspective	Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang
10	Safety Verification of Decision-Tree Policies in Continuous Time	Christian Schilling, Anna Lukina, Emir Demirović, Kim Guldstrand Larsen
11	Trans-Dimensional Generative Modeling via Jump Diffusion Models	Andrew Campbell, William Harvey, Christian Dietrich Weilbach, Valentin De Bortoli, Tom Rainforth, Arnaud Doucet
12	Break It Down: Evidence for Structural Compositionality in Neural Networks	Michael A. Lepori, Thomas Serre, Ellie Pavlick
13	DreamHuman: Animatable 3D Avatars from Text	Nikos Kolotouros, Thiemo Alldieck, Andrei Zanfir, Eduard Gabriel Bazavan, Mihai Fieraru, Cristian Sminchisescu
14	Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation	Kirill Neklyudov, Jannes Nys, Luca Thiede, Juan Felipe Carrasquilla Alvarez, qiang liu, Max Welling, Alireza Makhzani
15	PRODIGY: Enabling In-context Learning Over Graphs	Qian Huang, Hongyu Ren, Peng Chen, Gregor KrŽmanc, Daniel Zeng, Percy Liang, Jure Leskovec
16	Explore In-Context Learning for 3D Point Cloud Understanding	Zhongbin Fang, Xiangtai Li, Xia Li, Joachim M. Buhmann, Chen Change Loy, Mengyuan Liu
17	Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics	Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty
18	Coherent Soft Imitation Learning	Joe Watson, Sandy Huang, Nicolas Heess
19	Deep Reinforcement Learning with Plasticity Injection	Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto
20	Saddle-to-Saddle Dynamics in Diagonal Linear Networks	Scott Pesme, Nicolas Flammarion
21	GloptiNets: Scalable Non-Convex Optimization with Certificates	Gaspard Beugnot, Julien Mairal, Alessandro Rudi
22	Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization	Liang Zhang, Junchi YANG, Amin Karbasi, Niao He
23	Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision	Ayush Tewari, Tianwei Yin, George Cazenavette, Semon Rezchikov, Joshua B. Tenenbaum, Fredo Durand, William T. Freeman, Vincent Sitzmann
24	Theoretical and Practical Perspectives on what Influence Functions Do	Andrea Schioppa, Katja Filippova, Ivan Titov, Polina Zablotskaia
25	Multi Time Scale World Models	Vaisakh Shaj, Saleh GHOLAM ZADEH, Ozan Demir, Luiz Ricardo Douat, Gerhard Neumann
26	Inferring the Future by Imagining the Past	Kartik Chandra, Tony Chen, Tzu-Mao Li, Jonathan Ragan-Kelley, Joshua B. Tenenbaum
27	What Planning Problems Can A Relational Neural Network Solve?	Jiayuan Mao, Tomás Lozano-Pérez, Joshua B. Tenenbaum, Leslie Pack Kaelbling
28	Supervised Pretraining Can Learn In-Context Reinforcement Learning	Jonathan Lee, Annie Xie, Aldo Pacchiano, Yash Chandak, Chelsea Finn, Ofir Nachum, Emma Brunskill
29	Semi-Supervised Domain Generalization with Known and Unknown Classes	Lei Zhang, Ji-Fu Li, Wei Wang
30	Tight Risk Bounds for Gradient Descent on Separable Data	Matan Schliserman, Tomer Koren
31	Learning Universal Policies via Text-Guided Video Generation	Yilun Du, Sherry Yang, Bo Dai, Hanjun Dai, Ofir Nachum, Joshua B. Tenenbaum, Dale Schuurmans, Pieter Abbeel
32	Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusion	Yash Sanjay Bhalgat, Iro Laina, Joao F. Henriques, Andrea Vedaldi, Andrew Zisserman
33	Learning Layer-wise Equivariances Automatically using Gradients	Tycho F.A. van der Ouderaa, Alexander Immer, Mark van der Wilk
34	Stable Nonconvex-Nonconcave Training via Linear Interpolation	Thomas Pethick, Wanyun Xie, Volkan Cevher
35	A Dynamical System View of Langevin-Based Non-Convex Sampling	Mohammad Reza Karimi Jaghargh, Ya-Ping Hsieh, Andreas Krause
36	On the Minimax Regret for Online Learning with Feedback Graphs	Khaled Eldowa, Emmanuel Esposito, Tommaso Cesari, Nicolò Cesa-Bianchi
37	Full-Atom Protein Pocket Design via Iterative Refinement	ZAIXI ZHANG, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu
38	Expressive Sign Equivariant Networks for Spectral Geometric Learning	Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron
39	4M: Massively Multimodal Masked Modeling	David Mizrahi, Roman Bachmann, Oguzhan Fatih Kar, Teresa Yeo, Mingfei Gao, Afshin Dehghan, Amir Zamir
40	Implicit Variational Inference for High-Dimensional Posteriors	Anshuk Uppal, Kristoffer Stensbo-Smidt, Wouter Boomsma, Jes Frellsen
41	ARTree: A Deep Autoregressive Model for Phylogenetic Inference	Tianyu Xie, Cheng Zhang
42	PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers	Phillip Lippe, Bastiaan S. Veeling, Paris Perdikaris, Richard E Turner, Johannes Brandstetter
43	ProPILE: Probing Privacy Leakage in Large Language Models	Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, Seong Joon Oh
44	Scale Alone Does not Improve Mechanistic Interpretability in Vision Models	Roland S. Zimmermann, Thomas Klein, Wieland Brendel
45	Alternation makes the adversary weaker in two-player games	Volkan Cevher, Ashok Cutkosky, Ali Kavis, Georgios Piliouras, Stratis Skoulakis, Luca Viano
46	A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation	Thomas FEL, Victor Boutin, Louis Béthune, Remi Cadene, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre
47	Sharp Spectral Rates for Koopman Operator Learning	Vladimir R Kostic, Karim Lounici, Pietro Novelli, massimiliano pontil
48	Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models	Siu Lun Chau, Krikamol Muandet, Dino Sejdinovic
49	SE(3) Equivariant Augmented Coupling Flows	Laurence Illing Midgley, Vincent Stimper, Javier Antoran, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
50	Regularization properties of adversarially-trained linear regression	Antonio H. Ribeiro, Dave Zachariah, Francis Bach, Thomas B. Schön
51	MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting	Felix Biggs, Antonin Schrab, Arthur Gretton
52	Leveraging sparse and shared feature activations for disentangled representation learning	Marco Fumero, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolá , Stefano Soatto, Bernhard Schölkopf, Francesco Locatello
53	ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets	Damien Teney, LIN Yong, Seong Joon Oh, Ehsan Abbasnejad
54	Tree-Based Diffusion Schrödinger Bridge with Applications to Wasserstein Barycenters	Maxence Noble, Valentin De Bortoli, Arnaud Doucet, Alain Durmus
55	Episodic Multi-Task Learning with Heterogeneous Neural Processes	Jiayi Shen, Xiantong Zhen, Cheems Wang, Marcel Worring
56	Squared Neural Families: A New Class of Tractable Density Models	Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic
57	Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures	Runa Eschenhagen, Alexander Immer, Richard E Turner, Frank Schneider, Philipp Hennig
58	Honesty Is the Best Policy: Defining and Mitigating AI Deception	Francis Rhys Ward, Francesca Toni, Francesco Belardinelli, Tom Everitt
59	Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics	Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Kacper Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noe, Ryota Tomioka
60	In-Context Impersonation Reveals Large Language Models' Strengths and Biases	Leonard Salewski, Stephan Alaniz, Isabel Rio-Torto, Eric Schulz, Zeynep Akata
61	Participatory Personalization in Classification	Hailey James, Chirag Nagpal, Katherine A Heller, Berk Ustun
62	Zero-shot causal learning	Hamed Nilforoshan, Michael Moor, Yusuf H Roohani, Yining Chen, Anja Å urina, Michihiro Yasunaga, Sara Oblak, Jure Leskovec
63	Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model	Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
64	Dense and Aligned Captions (DAC) Promote Compositional Reasoning in VL Models	Sivan Doveh, Assaf Arbelle, Sivan Harary, Roei Herzig, Donghyun Kim, Paola Cascante-Bonilla, Amit Alfassy, Rameswar Panda, Raja Giryes, Rogerio Feris, Shimon Ullman, Leonid Karlinsky
65	One-step differentiation of iterative algorithms	Jerome Bolte, Edouard Pauwels, Samuel Vaiter
66	Physics-Driven ML-Based Modelling for Correcting Inverse Estimation	Ruiyuan Kang, Tingting Mu, Panos Liatsis, Dimitrios Kyritsis
67	AbDiffuser: full-atom generation of in-vitro functioning antibodies	Karolis Martinkus, Jan Ludwiczak, WEI-CHING LIANG, Julien Lafrance-Vanasse, Isidro Hotzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas
68	The Exact Sample Complexity Gain from Invariances for Kernel Regression	Behrooz Tahmasebi, Stefanie Jegelka
69	Compression with Bayesian Implicit Neural Representations	Zongyu Guo, Gergely Flamich, Jiajun He, Zhibo Chen, JoséMiguel Hernández-Lobato
70	A Cross-Moment Approach for Causal Effect Estimation	Yaroslav Kivva, Saber Salehkaleybar, Negar Kiyavash
71	The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs	Laura Eline Ruis, Akbir Khan, Stella Biderman, Sara Hooker, Tim Rocktäschel, Edward Grefenstette
72	What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement.	Yotam Alexander, Nimrod De La Vega, Noam Razin, Nadav Cohen
73	Learning to Receive Help: Intervention-Aware Concept Embedding Models	Mateo Espinosa Zarlenga, Katherine M. Collins, Krishnamurthy Dj Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik
74	QuantSR: Accurate Low-bit Quantization for Efficient Image Super-Resolution	Haotong Qin, Yulun Zhang, Yifu Ding, Yifan liu, Xianglong Liu, Martin Danelljan, Fisher Yu
75	From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces	Peter Shaw, Mandar Joshi, James Cohan, Jonathan Berant, Panupong Pasupat, Hexiang Hu, Urvashi Khandelwal, Kenton Lee, Kristina Toutanova
76	Efficient Online Clustering with Moving Costs	Dimitris Christou, EFSTRATIOS PANTELEIMON SKOULAKIS, Volkan Cevher
77	Learning Functional Transduction	Mathieu Chalvidal, Thomas Serre, Rufin VanRullen
78	Computing a human-like reaction time metric from stable recurrent vision models	Lore Goetschalckx, Lakshmi Narasimhan Govindarajan, Alekh Karkada Ashok, Aarit Ahuja, David Sheinberg, Thomas Serre

NeurIPS 2023 oral

#	Paper Title	List of authors (ELLIS members in bold)
1	Ordering-based Conditions for Global Convergence of Policy Gradient Methods	Jincheng Mei, Bo Dai, Alekh Agarwal, Mohammad Ghavamzadeh, Csaba Szepesvari, Dale Schuurmans
2	A Measure-Theoretic Axiomatisation of Causality	Junhyung Park, Simon Buchholz, Bernhard Schölkopf, Krikamol Muandet
3	Learning Linear Causal Representations from Interventions under General Nonlinear Mixing	Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Kumar Ravikumar
4	Clifford Group Equivariant Neural Networks	David Ruhe, Johannes Brandstetter, Patrick Forré
5	Abide by the law and follow the flow: conservation laws for gradient flows	Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
6	Rotating Features for Object Discovery	Sindy Löwe, Phillip Lippe, Francesco Locatello, Max Welling
7	Entropic Neural Optimal Transport via Diffusion Processes	Nikita Gushchin, Alexander Kolesov, Alexander Korotin, Dmitry P. Vetrov, Evgeny Burnaev
8	A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods	Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch
9	Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures	Hamish Flynn, David Reeb, Melih Kandemir, Jan Peters
10	Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent	Jihao Andreas Lin, Javier Antoran, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin
11	How to Turn Your Knowledge Graph Embeddings into Generative Models	Lorenzo Loconte, Nicola Di Mauro, Robert Peharz, Antonio Vergari
12	Causal normalizing flows: from theory to practice	Adrián Javaloy, Pablo Sanchez Martin, Isabel Valera
13	A U-turn on Double Descent: Rethinking Parameter Counting in Statistical Learning	Alicia Curth, Alan Jeffares, Mihaela van der Schaar
14	Online RL in Linearly q^\pi-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore	Gellért Weisz, András György, Csaba Szepesvari
15	Direct Preference Optimization: Your Language Model is Secretly a Reward Model	Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, Chelsea Finn
16	Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment	Royi Rassin, Eran Hirsch, Daniel Glickman, Shauli Ravfogel, Yoav Goldberg, Gal Chechik
17	Characteristic Circuits	Zhongjie Yu, Martin Trapp, Kristian Kersting
18	DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models	Tsun-Hsuan Wang, Juntian Zheng, Pingchuan Ma, Yilun Du, Byungchul Kim, Andrew Everett Spielberg, Joshua B. Tenenbaum, Chuang Gan, Daniela Rus
19	Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition	Samuel Dooley, Rhea Sanjay Sukthanker, John P Dickerson, Colin White, Frank Hutter, Micah Goldblum
20	Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models	Guillermo Ortiz-Jimenez, Alessandro Favero, Pascal Frossard
21	Going beyond persistent homology using persistent homology	Johanna Immonen, Amauri Souza, Vikas Garg

NeurIPS 2023 Datasets and Benchmarks Poster

#	Paper Title	List of authors (ELLIS members in bold)
1	AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems	Jeroen Berrevoets, Daniel Jarrett, Alex James Chan, Mihaela van der Schaar
2	PIXIU: A Comprehensive Benchmark, Instruction Dataset and Large Language Model for Finance	Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, Jimin Huang
3	A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning	Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
4	Synthcity: a benchmark framework for diverse use cases of tabular synthetic data	Zhaozhi Qian, Rob Davis, Mihaela van der Schaar
5	Temporal Graph Benchmark for Machine Learning on Temporal Graphs	Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany
6	FIND: A Function Description Benchmark for Evaluating Interpretability Methods	Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba
7	Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union	Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko
8	AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web	Michael Sejr Schlichtkrull, Zhijiang Guo, Andreas Vlachos
9	URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates	Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Enkelejda Kasneci
10	Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark	Lasse Hansen, Nabeel Seedat, Mihaela van der Schaar, Andrija Petrovic
11	VidChapters-7M: Video Chapters at Scale	Antoine Yang, Arsha Nagrani, Ivan Laptev, Josef Sivic, Cordelia Schmid
12	QATCH: Benchmarking SQL-centric tasks with Table Representation Learning Models on Your Data	Simone Papicchio, Paolo Papotti, Luca Cagliero
13	Learning to Taste: A Multimodal Wine Dataset	Thoranna Bender, Simon Moe SÃ¸rensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, SÃ¸ren Hauberg, Serge Belongie, Frederik RahbÃ¦k Warburg
14	ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design	Pascal Notin, Aaron W Kollasch, Daniel Ritter, Lood Van Niekerk, Steffan Paul, Han Spinner, Nathan J Rollins, Ada Shaw, Rose Orenbuch, Ruben Weitzman, Jonathan Frazer, Mafalda Dias, Dinko Franceschi, Yarin Gal, Debora Susan Marks
15	Learning Human Action Recognition Representations Without Real Humans	Howard Zhong, Samarth Mishra, Donghyun Kim, SouYoung Jin, Rameswar Panda, Hilde Kuehne, Leonid Karlinsky, Venkatesh Saligrama, Aude Oliva, Rogerio Feris
16	OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents	Hugo LaurenÃ§on, Lucile Saulnier, Leo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M Rush, Douwe Kiela, Matthieu Cord, Victor Sanh
17	FLAIR : a Country-Scale Land Cover Semantic Segmentation Dataset From Multi-Source Optical Imagery	Anatol Garioud, Nicolas Gonthier, Loic Landrieu, Apolline De Wit, Marion Valette, Marc PoupÃ©e, Sebastien Giordano, Boris Wattrelos
18	DataPerf: Benchmarks for Data-Centric AI Development	Mark Mazumder, Colby Banbury, Xiaozhe Yao, Bojan KarlaÅ¡, William A Gaviria Rojas, Sudnya Diamos, Greg Diamos, Lynn He, Alicia Parrish, Hannah Rose Kirk, Jessica Quaye, Charvi Rastogi, Douwe Kiela, David Jurado, David Kanter, Rafael Mosquera, Will Cukierski, Juan Ciro, Lora Aroyo, Bilge Acun, Lingjiao Chen, Mehul Smriti Raje, Max Bartolo, Sabri Eyuboglu, Amirata Ghorbani, Emmett Daniel Goodman, Addison Howard, Oana Inel, Tariq Kane, Christine Kirkpatrick, D. Sculley, Tzu-Sheng Kuo, Jonas Mueller, Tristan Thrush, Joaquin Vanschoren, Margaret Warren, Adina Williams, Serena Yeung, Newsha Ardalani, Praveen Paritosh, Ce Zhang, James Y. Zou, Carole-Jean Wu, Cody Coleman, Andrew Ng, Peter Mattson, Vijay Janapa Reddi
19	The Drunkard´s Odometry: Estimating Camera Motion in Deforming Scenes	David Recasens, Martin R. Oswald, Marc Pollefeys, Javier Civera
20	GEO-Bench: Toward Foundation Models for Earth Monitoring	Alexandre Lacoste, Nils Lehmann, Pau Rodriguez, Evan David Sherwin, Hannah Kerner, BjÃ¶rn LÃ¼tjens, Jeremy Andrew Irvin, David Dao, Hamed Alemohammad, Alexandre Drouin, Mehmet Gunturkun, Gabriel Huang, David Vazquez, Dava Newman, Yoshua Bengio, Stefano Ermon, Xiao Xiang Zhu
21	Perception Test: A Diagnostic Benchmark for Multimodal Video Models	Viorica Patraucean, Lucas Smaira, Ankush Gupta, Adria Recasens Continente, Larisa Markeeva, Dylan Sunil Banarse, Skanda Koppula, Joseph Heyward, Mateusz Malinowski, Yi Yang, Carl Doersch, Tatiana Matejovicova, Yury Sulsky, Antoine Miech, Alexandre FrÃ©chette, Hanna Klimczak, Raphael Koster, Junlin Zhang, Stephanie Winkler, Yusuf Aytar, Simon Osindero, Dima Damen, Andrew Zisserman, Joao Carreira
22	StoryBench: A Multifaceted Benchmark for Continuous Story Visualization	Emanuele Bugliarello, Hernan Moraldo, Ruben Villegas, Mohammad Babaeizadeh, Mohammad Taghi Saffar, Han Zhang, Dumitru Erhan, Vittorio Ferrari, Pieter-Jan Kindermans, Paul Voigtlaender
23	What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation	Benedikt Blumenstiel, Johannes Jakubik, Hilde Kuehne, Michael VÃ¶ssing
24	Estimating Generic 3D Room Structures from 2D Annotations	Denys Rozumnyi, Stefan Popov, Kevis-kokitsi Maninis, Matthias Nießner, Vittorio Ferrari
25	NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations	Varun Jampani, Kevis-kokitsi Maninis, Andreas Engelhardt, Arjun Karpur, Karen Truong, Kyle Sargent, Stefan Popov, Andre Araujo, Ricardo Martin Brualla, Kaushal Patel, Daniel Vlasic, Vittorio Ferrari, Ameesh Makadia, Ce Liu, Yuanzhen Li, Howard Zhou
26	Humans in Kitchens: A Dataset for Multi-Person Human Motion Forecasting with Scene Context	Julian Alexander Tanke, Oh-Hun Kwon, Felix Benjamin Mueller, Andreas Doering, Juergen Gall
27	SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning	Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob Nicolaus Foerster, Shimon Whiteson
28	Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties	Hsiao-Yu Tung, Mingyu Ding, Zhenfang Chen, Daniel Bear, Chuang Gan, Joshua B. Tenenbaum, Daniel LK Yamins, Judith E Fan, Kevin A. Smith
29	Benchmarking Robustness of Adaptation Methods on Pre-trained Vision-Language Models	Shuo Chen, Jindong Gu, Zhen Han, Yunpu Ma, Philip Torr, Volker Tresp
30	ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning	Julia Kaltenborn, Charlotte Emilie Elektra Lange, Venkatesh Ramesh, Philippe Brouillard, Yaniv Gurwicz, Chandni Nagda, Jakob Runge, Peer Nowack, David Rolnick
31	ProteinShake: Building datasets and benchmarks for deep learning on protein structures	Tim Kucera, Carlos Oliver, Dexiong Chen, Karsten Borgwardt
32	EPIC Fields: Marrying 3D Geometry and Video Understanding	Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu, David Fouhey, Iro Laina, Diane Larlus, Dima Damen, Andrea Vedaldi

NeurIPS 2023 Datasets and Benchmarks Spotlight

#	Paper Title	List of authors (ELLIS members in bold)
1	Holistic Evaluation of Text-to-Image Models	Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Benita Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Li Fei-Fei, Jiajun Wu, Stefano Ermon, Percy Liang
2	Renku: a platform for sustainable data science	Rok Roškar, Chandrasekhar Ramakrishnan, Michele Volpi, Fernando Perez-Cruz, Lilian Gasser, Firat Ozdemir, Patrick Paitz, Mohammad Alisafaee, Philipp Fischer, Ralf Grubenmann, Eliza Jean Harris, Tasko Olevski, Carl Remlinger, Luis Salamanca, Elisabet Capon Garcia, Lorenzo Cavazzi, Jakub Chrobasik, Darlin Andrea Cordoba Osnas, Alessandro Degano, Jimena Dupre, Wesley Johnson, Eike Kettner, Laura Kinkead, Sean Murphy, Flora Thiebaut, Olivier Verscheure
3	DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology	Marco Aversa, Gabriel Nobis, Miriam HÃ¤gele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala
4	The Waymo Open Sim Agents Challenge	Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Zeyu Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov

NeurIPS 2023 Datasets and Benchmarks Oral

#	Paper Title	List of authors (ELLIS members in bold)
1	DataComp: In search of the next generation of multimodal datasets	Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
2	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation	Sungduk Yu, Walter Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus Christopher Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles I Stern, Tom Beucler, Bryce Harrop, Benjamin R Hillman, Andrea Jenney, Savannah Ferretti, Nana Liu, Anima Anandkumar, Noah D Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C Bader, Pierre Baldi, Elizabeth Barnes, Christopher Bretherton, Peter Caldwell, Wayne Chuang, Yilun Han, YU HUANG, Fernando Iglesias-Suarez, Sanket Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David Randall, Sara Shamekh, Mark A Taylor, Nathan Urban, Janni Yuval, Guang Zhang, Michael Pritchard
3	Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean	Spyros Kondylatos, Ioannis Prapas, Gustau Camps-Valls, Ioannis Papoutsis

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