Friday evening (Chaired by Anne Churchland)
7 pm — Session 1 — Brains and machines
David Heeger, NYU – ORGaNICs: An idea of working memory in brains and machines
Eve Marder, Brandeis – Surprising sturdiness and reliability in neuronal circuits
Yoshua Bengio, Université de Montréal – Bridging the space between deep learning and neuroscience
‘life was imple’ (Chaired by David Heeger)
8 am — Session 2 — Biological and artificial mechanisms
Blaise Agüera y Arcas, Google – Learning in your area and globally
Mu-ming Poo, Chinese Academy of Sciences – Synaptic plasticity and brain-inspired machine learning
Terry Sejnowski, Salk Institute – The worldwide brain
Coffee break
10.30 am — Session 3 — Action
Leslie Pack Kaelbling, Durch – Making robots behave
Daniel Wolpert, Cambridge – Probabilistic types of sensorimotor control
Matteo Carandini, UCL – Testing the textbook type of thinking processes
Lunch time
Saturday mid-day (Chaired by Matteo Carandini)
2 pm — Session 4 — Cognition
Stanislas Dehaene, Collège de France – What’s awareness, and may machines get it?
Anne Churchland, Cold Spring Harbor Laboratory – Assessing massive cortical systems during decision-making
Matthew Botvinick, DeepMind – Meta-learning in brains and machines
Coffee break
4.30 pm — Session 5 — Navigating and Remembering
David Tank, Princeton – Characterizing neural dynamics during navigation and decision-making
Ila Fiete, College of Texas, Austin – Understanding and decoding the brain’s spatial navigation circuits
Sunday morning (Chaired by Tony Movshon)
8 am — Session 6 — Vision 1
Yann LeCun, Facebook – What would be the concepts of learning in newborns?
Jim DiCarlo, Durch – Reverse engineering visual intelligence
Eero Simoncelli, NYU – Perceptual implications of hierarchical visual models
Coffee break
10.30 am — Session 7 — Vision 2
Adrienne Fairhall, College of Washington – Rules of adaptation across cortex
Nicole Rust, College of Pennsylvania – Adaptation like a canonical mechanism for memory
Shimon Ullman, Weizmann Institute of Science – Image understanding beyond object recognition
Lunch time
Sunday mid-day (Chaired by Anne Churchland)
2 pm — Session 8 — Learning 1
Kenji Doya, Okinawa Institute of Science – Neural circuits for reinforcement learning and mental simulation
Zach Mainen, Fundação Champalimaud – Serotonin and also the regulating neural inference and learning
Upi Bhalla, National Center for Biological Sciences, Tata Institute of Fundamental Research – Molecular computation: another deep network within the brain
Coffee break
4.30 pm — Session 9 — Learning 2
Greg Corrado, Google – Practical intelligence and skeptical minds
Josh Tenenbaum, MIT – Building machines that learn and think like people
Ray Abbott, Columbia – Fly AI
Resourse: http://gias.nyu.edu/canonical-computation-brains-machines-2018/