Conférenciers et instructeurs

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Conférenciers confirmés pour MAIN 2018

Yoshua Bengio, MILA, Computer Science and Operations Research Dept, Université de Montréal, Montreal, Canada
Titre: Inspiration from Brains for Deep Learning and Inspiration from Deep Learning for Brains
Blake Richards, Department of Biological Sciences and Department of Cell and Systems Biology, University of Toronto
Titre: A deep learning recipe for neuroscience
Irina Rish, AI Foundations Learning, IBM Watson Research, NY, USA
Modeling Brain Dynamics: van der Pol, LSTMs and beyond

Sebastian Stober, Machine Learning in Cognitive Science Group, Universität Potsdam, Potsdam, Germany
Titre: Bridging Deep Learning & Cognitive Neuroscience - From Method Transfer to Hybrid Modeling
Danilo Bzdok, Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Germany
Titre: Statistics wars in imaging neuroscience: classical inference vs. pattern generalization
Yves Fregnac, Unité de Neurosciences, Information et Complexité, CNRS, Gif-sur-Yvette, France.
Titre: From Big-data driven simulation of the Brain and artificial intelligence to the myth of transhumanism
Pascal Vincent, MILA and Facebook, Computer Science and Operations Research Dept, Université de Montréal, Canada
Titre: Introduction to deep learning
Michael Mozer, Univ Boulder Colorado, USA
Titre: The role of access consciousness in humans and machines
Radoslaw Martin Cichy, Neural Dynamics of Visual Cognition Group, Free University Berlin, Berlin, Germany
Titre: Do DNNs in cogntive science make sense?
Pamela Douglas, Center for Cognitive Neuroscience, UCLA, Los Angeles, United States
Titre: Building Brain Computational Models
Alexandre Gramfort, INRIA, Parietal Team , Université Paris Saclay, France
Titre: Learning representations from neural signals
Doina Precup, McGill and DeepMind, Montreal, Canada
Titre: Hierarchical Reinforcement Learning in computers and brains
Daniel Yamins, NeuroAILab, Stanford Neurosciences Institute, Stanford University, CA, USA
Titre: Cognitively Inspired Artificial Intelligence for Neuroscience
Tatyana Sharpee, Computational Neurobiology Laboratory, Salk Institute for Biological Studies, San Diego, CA, USA
Titre: Elements of cortical computation that enhance robustness of object recognition
Ben D Huh, MIT-IBM Watson AI Lab, Cambridge, MA, USA
Titre: Exploring the space of spike-based computationsv

Instructeurs durant les sessions de formation

Andrew Doyle, Joseph Paul Cohen, Thomas Funck, Christopher Beckham
Pierre Bellec, Amal Boukhdhir, Elizabeth DuPré, Greg Kiar, Basile Pinsard, Jacob Vogel