– global institute for advanced study

- global institute for advanced study and machines    

           Coffee break

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

- global institute for advanced study Understanding and decoding

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/

Analyticity results for the Euler and Navier-Stokes equations – Guher Camliyurt