ELLIS Reading Groups
As part of its educational activities, ELLIS aims to connect PhDs and postdocs in the network and supports them in creating opportunities to discuss science.
Several student-led reading groups on machine learning-related topics meet regularly to discuss a paper the group previously voted on. ELLIS Reading Groups are initiated and organized by ELLIS PhD students and postdocs across Europe.
1. Human-Centric Machine Learning (HCML)
The HCML reading group aims to gather researchers and students interested in both getting a wide vision of the topic and also deeply diving into it. Reading papers about different topics inside HCML, and also discussing new problem set-ups, different approaches, and sources of bias will lead us to a broad understanding of how algorithmic and human decisions influence each other.
Chairs: Adrián Arnaiz-Rodríguez, Aditya Gulati, Gergely Németh, Piera Riccio (all University of Alicante)
An overview of past and upcoming sessions is provided on the group's webpage.
2. Mathematics of Deep Learning
The Mathematics of Deep Learning group is for discussing the theoretical background of the state-of-the-art deep neural networks. This theory is aiming at explaining the mechanisms behind the training, generalization, architecture, initialization choosing, etc. This reading group is not restricted by any particular application, so various tasks can be considered, ranging from the purely theoretical linear networks to (current) state-of-the-art transformer networks for natural language processing. The group’s main goal is to keep up with the most advanced areas of research in understanding mathematics behind deep neural networks and their optimization.
Chairs: Linara Adilova (Ruhr University Bochum), Oishi Deb (University of Oxford), Sidak Pal Singh (ETH Zurich)
Find more information about the group's sessions on this website.
3. Computer Vision and Beyond
The field of Computer Vision has witnessed significant evolution in recent decades, from the emergence of Vision Transformers to the development of powerful Generative AI models. This reading group aims to explore the latest research within and beyond this field, encompassing topics from deep learning fundamentals to cutting-edge Vision-Language Models. Our main goal is to stay abreast of the most advanced areas in understanding the concepts underpinning deep neural networks and their diverse applications in computer vision.
Chair: Oishi Deb (University of Oxford)
4. ELLIS UniReps Speaker Series
The ELLIS UniReps Speaker Series explores the phenomenon of representational alignment, where different neural models—both biological and artificial—develop similar internal representations when exposed to comparable stimuli. This raises key theoretical and practical questions: When do similar representations emerge across models? Why does this alignment occur, and what underlying principles drive it? How can we leverage this alignment to explore applications such as model merging, model re-use, and fine-tuning?
Each monthly session features two talks: 1) Keynote talk – A broad overview by a senior researcher, providing context on a key topic; 2) Flash talk – A focused presentation by an early-career researcher (such as a PhD student or postdoc), highlighting recent findings or ongoing work.
The series will introduce participants to core topics in deep learning, neuroscience, cognitive science, and mathematics and will give opportunity for early-career researchers to share their work and foster interdisciplinary discussions across research fields listed above.
Chairs: Marco Fumero (IST Austria), Clementine Domine (UCL Gatsby), Irene Cannistraci (ETH), Dingling Yao (IST Austria)
Find more information about the group's sessions on this website.
For any further questions about the Reading Groups or the ELLIS PhD & Postdoc Program, please contact phd@ellis.eu.
