ELLIS Pre-NeurIPS Fest 2023

11 ELLIS units across Europe organized pre-NeurIPS poster sessions to showcase and discuss their research community's contributions to the flagship conference in New Orleans.

Find below a list of posters presented at some of those events.

Poster Title	Author List
ELLIS Unit Darmstadt
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion	Al-Hafez, Firas; Zhao, Guoping; Peters, Jan; Tateo, Davide
Tactile Active Texture Recognition With Vision-Based Tactile Sensors	Boehm, Alina; Schneider, Tim; Belousov, Boris; Kshirsagar, Alap; Lin, Lisa; Doerschner, Katja; Drewing, Knut; Rothkopf, Constantin A.; Peters, Jan
SEGA: Instructing Text-to-Image Models using Semantic Guidance	Brack, Manuel; Friedrich, Felix; Hintersdorf, Dominik; Struppek, Lukas; Schramowski, Patrick; Kersting, Kristian
Pseudo-Likelihood Inference	Gruner, Theo; Belousov, Boris; Muratore, Fabio; Palenicek, Daniel; Peters, Jan
Leveraging Diffusion-Based Image Variations for Robust Training on Poisoned Data	Struppek, Lukas; Hentschel, Martin B.; Poth, Clifton; Hintersdorf, Dominik; Kersting, Kristian
Do Not Marginalize Mechanisms, Rather Consolidate!	Willig, Moritz; Zečević, Matej; Dhami, Devendra; Kersting, Kristian
Characteristic Circuits	Yu, Zhongjie; Trapp, Martin; Kersting, Kristian
ELLIS Unit Helsinki
Characteristic Circuits	Zhongjie Yu · Martin Trapp · Kristian Kersting
Compositional Sculpting of Iterative Generative Processes	Timur Garipov · Sebastiaan De Peuter · Ge Yang · Vikas Garg · Samuel Kaski · Tommi Jaakkola
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning	Mhairi Dunion · Trevor McInroe · Kevin Sebastian Luck · Josiah Hanna · Stefano Albrecht
Continuous-Time Functional Diffusion Processes	Giulio Franzese · Giulio Corallo · Simone Rossi · Markus Heinonen · Maurizio Filippone · Pietro Michiardi
Going beyond persistent homology using persistent homology	Johanna Immonen · Amauri Souza · Vikas Garg
Learning Robust Statistics for Simulation-based Inference under Model Misspecification	Daolang Huang · Ayush Bharti · Amauri Souza · Luigi Acerbi · Samuel Kaski
Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States	Valerii Iakovlev · Markus Heinonen · Harri Lähdesmäki
Practical Differentially Private Hyperparameter Tuning with Subsampling	Antti Koskela · Tejas Kulkarni
Practical Equivariances via Relational Conditional Neural Processes	Daolang Huang · Manuel Haussmann · Ulpu Remes · ST John · Grégoire Clarté · Kevin Sebastian Luck · Samuel Kaski · Luigi Acerbi
Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond	Omar Chehab · Aapo Hyvarinen · Andrej Risteski
Temporal Causal Mediation through a Point Process: Direct and Indirect Effects of Healthcare Interventions	Çağlar Hızlı · ST John · Anne Juuti · Tuure Saarinen · Kirsi Pietiläinen · Pekka Marttinen
Thin and deep Gaussian processes	Daniel Augusto de Souza · Alexander Nikitin · ST John · Magnus Ross · Mauricio A Álvarez · Marc Deisenroth · João Paulo Gomes · Diego Mesquita · César Lincoln Mattos
LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer	Haoyu Chen, Hao Tang, Radu Timofte, Luc V Gool, Guoying Zhao
ELLIS Unit Manchester
Physics-Driven ML-Based Modeling for Correcting Inverse Estimation	Kang, Ruiyuan; Mu, Tingting; Liatsis, Panos; Kyritsis, Dimitrios C.
Bi-directional Distribution Alignment for Transductive Zero-Shot Learning	Zhicai Wang, Yanbin Hao, Tingting Mu, Ouxiang Li, Shuo Wang, Xiangnan He
On the Modelling and Impact of Negative Edges in Graph Convolution Networks for Node Classification	Thu Trang Dinh · Julia Handl · Luis Ospina-Forero.
Understanding and Improving Ensemble Adversarial Defense	Yian Deng, Tingting Mu
SMACv2: An Improved Benchmark for Cooperative Reinforcement Learning	Benjamin Ellis, Jonathan Cook, Skander Moalla, Mikayel Samvelyan, Mingfei Sun, Anuj Mahajan, Jakob N. Foerster, Shimon Whiteson
ELLIS Unit Milan
Truncating Trajectories in Monte Carlo Policy Evaluation: an Adaptive Approach	Riccardo Poiani, Nicole Nobili, Alberto Maria Metelli, Marcello Restelli
Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning	Riccardo Zamboni, Alberto Maria Metelli, M. Restelli
On the Minimax Regret for Online Learning with Feedback Graphs	Khaled Eldowa, Emmanuel Esposito, Tom Cesari, Nicolò Cesa-Bianchi
Persuading Farsighted Receivers in MDPs: the Power of Honesty	Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi, Mirco Mutti
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
ELLIS Unit Trento
Flow Factorized Representation Learning, NeurIPS 2023	Y. Song, A. Keller, N. Sebe, and M. Welling
Discover and Align Taxonomic Context Priors for Open-world Semi-Supervised Learning, NeurIPS 2023	Y. Wang, Z. Zhong, P. Qiao, X. Cheng, X. Zheng, C. Liu, N. Sebe, R. Ji, and J. Chen
Vocabulary-free Image Classification, NeurIPS 2023	A. Conti, E. Fini, M. Mancini, P. Rota, Y. Wang, E. Ricci.
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts, NeurIPS 2023	E. Marconato, S. Teso, A. Vergari, A. Passerini
Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships, NeurIPS 2023	A. Chaudhuri, M. Mancini, Z. Akata, A. Dutta,
ELLIS Unit Tübingen
Causal Component Analysis	Liang Wendong, Armin Kekić, Julius von Kügelgen, Simon Buchholz, Michel Besserve, Luigi Gresele, Bernhard Schölkopf
Regularity as Intrinsic Reward for Free Play	Cansu Sancaktar, Justus Piater, Georg Martius
Beyond Average Return in Markov Decision Processes	Alexandre Marthe, Aurélien Garivier, Claire Vernade
Reinforcement Learning with Simple Sequence Priors	Tankred Saanum, Noemi Elteto, Peter Dayan, Marcel Binz, Eric Schulz
RDumb: A simple approach that questions our progress in continual test-time adaptation	Ori Press, Steffen Schneider, Matthias Kümmerer, Matthias Bethge
Online Learning under Adversarial Nonlinear Constraints	Pavel Kolev, Georg Martius, Michael Muehlebach
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities	Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Compositional Generalization from First Principles	Thaddäus Wiedemer, Prasanna Mayilvahanan, Matthias Bethge, Wieland Brendel
Scale Alone Does not Improve Mechanistic Interpretability	Roland S. Zimmermann, Thomas Klein, Wieland Brendel
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
In-Context Impersonation Reveals Large Language Models' Strengths and Biases	Leonard Salewski, Isabel Rio-Torto, Stephan Alaniz, Eric Schulz, Zeynep Akata
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images	Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
SE(3) Equivariant Augmented Coupling Flows	Laurence Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato
Modulated Neural ODEs	Ilze Amanda Auzina, Çağatay Yıldız, Sara Magliacane, Matthias Bethge, Efstratios Gavves
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation	Richard Gao, Michael Deistler, Jakob H Macke
Flow Matching for Scalable Simulation-Based Inference	Maximilian Dax, Jonas Wildberger, Simon Buchholz, Stephen R. Green, Jakob H. Macke, Bernhard Schölkopf
URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates	Michael Kirchhof, Bálint Mucsányi, Seong Joon Oh, Dr. Enkelejda Kasneci
ELLIS Unit Warsaw
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders	Jan Dubiński, Stanisław Pawlak, Franziska Boenisch, Tomasz Trzciński, Adam Dziedzic
The Tunnel Effect: Building Data Representations in Deep Neural Networks	Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Miłoś, Tomasz Trzciński
Focused Transformer: Contrastive Training for Context Scaling	Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Miłoś
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery	Mateusz Olko, Michał Zając, Aleksandra Nowak, Nino Scherrer, Yashas Annadani, Stefan Bauer, Łukasz Kuciński, Piotr Miłoś
Revisiting Supervision for Continual Representation Learning	Daniel Marczak, Sebastian Cygert, Tomasz Trzciński, Bartłomiej Twardowski
Augmentation-aware Self-supervised Learning with Conditioned Projector	Marcin Przewięźlikowski, Mateusz Pyla, Bartosz Zieliński, Bartłomiej Twardowski, Jacek Tabor
ELLIS Unit Zurich
From SGD to Adaptive Methods: Benefits of Adaptive Gradient Techniques	Junchi Yang, Xiang Li, Ilyas Fatkhullin, Niao He
Parameter-Agnostic Optimization under Relaxed Smoothness	Florian Hübler, Junchi Yang, Xiang Li, Niao He
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization	Liang Zhang, Junchi Yang, Amin Karbasi, Niao He
Scaling MLPs: A Tale of Inductive Bias	Gregor Bachmann, Sotiris Anagnostidis, Thomas Hofmann
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers	Solis Angosi, Dario Paulo, Luca Biggio, Lorenzo Noci, Aurelien Lucchi, Thomas Hofmann
The Shaped Transformer:Attention Models in the Infinite Depth-and-Width Limit at Initialization	Lorenzo Noci, Chuning Li, Mufan (Bill) Li, Bobby He, Thomas Hofmann, Chris Maddison, Daniel Roy
On the Importance of Step-wise Embeddings...	Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch
Multi-modal Graph Learning over UMLS Knowledge Graphs	Manuel Burger, Gunnar Rätsch, Rita Kuznetsova

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