activity
20192021
most citedInverse Rational Control with Partially Observable Continuous Nonlinear Dynamics

16 citations · 43 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG20219 cited

A Unified Paths Perspective for Pruning at Initialization

Thomas Gebhart, Udit Saxena, Paul Schrater

A number of recent approaches have been proposed for pruning neural network parameters at initialization with the goal of reducing the size and computational burden of models while…

q-bio.NC2020

The structure of behavioral data

Aurélien Defossez, Morteza Ansarinia, Brice Clocher +3

For more than a century, scientists have been collecting behavioral data--an increasing fraction of which is now being publicly shared so other researchers can reuse them to replic…

q-bio.OT20201 cited

Neuromatch Academy: Teaching Computational Neuroscience with global accessibility

Tara van Viegen, Athena Akrami, Kate Bonnen +32

Neuromatch Academy designed and ran a fully online 3-week Computational Neuroscience summer school for 1757 students with 191 teaching assistants working in virtual inverted (or fl…

cs.LG202016 cited

Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics

Minhae Kwon, Saurabh Daptardar, Paul Schrater +1

A fundamental question in neuroscience is how the brain creates an internal model of the world to guide actions using sequences of ambiguous sensory information. This is naturally…

q-bio.NC202014 cited

Appreciating the variety of goals in computational neuroscience

Konrad P. Kording, Gunnar Blohm, Paul Schrater +1

Within computational neuroscience, informal interactions with modelers often reveal wildly divergent goals. In this opinion piece, we explicitly address the diversity of goals that…

cs.AI2019

Inverse Rational Control with Partially Observable Continuous Nonlinear Dynamics

Saurabh Daptardar, Paul Schrater, Xaq Pitkow

Continuous control and planning remains a major challenge in robotics and machine learning. Neuroscience offers the possibility of learning from animal brains that implement highly…