MAIN Conference

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145 videos

Montreal AI and Neuroscience (MAIN) is an international conference organized by the UNIQUE Centre in collaboration with the Centre de Recherches Mathématique...

Latest Videos

Siva Reddy - “The role of memory in long chain-of-thought reasoning”

(Keynote #4) Alison Gopnik - Empowerment and Causal Learning in Humans and Machines

Declan Campbell “From seeing to thinking evaluating & improving visual reasoning in VLMs”

Panel discussion #2 The future of AI - The role of human cognition

(Keynote #3) - Yoshua Bengio - “Scientist AI disentangling agency and causal understanding”

Pablo Samuel Castro - The Formalism-Implementation Gap in Reinforcement Learning Research

Lune Bellec - AI Models of Human Brain and Behaviour During Naturalistic Videogame Play

Joao Sacramento - “Emergent temporal abstractions in autoregressive models enable hierarchical RL”

Choong-Wan Woo - “Pain, interoception, and life-inspired artificial intelligence”

Panel discussion #1 The future of Neuroscience - The role of AI

Ching Fang - From Memories to Maps Mechanisms of In-Context Reinforcement Learning in Transformers

Ida Momennejad - Studying Play What Games Reveal About Minds and Machines

(Keynote #1) - Andreas Tolias - Foundation models and digital twins of the brain

(Keynote #2) - SueYeon Chung - Untangling Emergence of Biological and Artificial Intelligence ...

Giulia Lioi - REVE a EEG foundation model adapted to any recording setup and task

Richard Naud - “Modular Organization of Electrical Fluctuations in the Mouse Brain”

Sara Solla - The dynamics of neural populations in the presence of heterogeneities

Rufin VanRullen - The Global Latent Workspace a model of cognition with AI applications

Joséphine Raugel “Similar Representations and Learning Dynamics Human Brains and Transformers

Laurent Perrinet - “A New Look for Convolutional Deep Networks”

Closing remarks & Brief closing address by Michelle Mckerrall

Keynote#6 - Eva Dyer - Large-scale pretraining on neural data allows for transfer across individuals

Guillaume Lajoie - Credit assignment in neural networks without plasticity

Alexander Meulmans - Multi-agent cooperation through learning-aware policy gradients

Panel discussion - Day 3 Are foundation models for neuroscience the next big thing

Keynote #5 - Laura Driscoll - Fast and slow learning in artificial and biological networks

Blake Richards - Brain-like learning with exponentiated gradients

Matthew Perich - A common neural basis for behavior across individuals and species

MAIN 2024 - Opening remarks

Patrick Mineault - Foundation models for neuroscience