no code implementations • 13 Nov 2023 • Grace W. Lindsay
Here I focus on grounding this goal in the specific question of how a given change in behavior is produced by a change in neural circuits or activity.
no code implementations • 14 Feb 2022 • Grace W. Lindsay
I provide here both a roadmap for performing this testing and a list of tools that are suitable to be tested on ANNs.
no code implementations • 3 Dec 2021 • Grace W. Lindsay, Josh Merel, Tom Mrsic-Flogel, Maneesh Sahani
Artificial neural systems trained using reinforcement, supervised, and unsupervised learning all acquire internal representations of high dimensional input.
no code implementations • 15 Dec 2020 • Tara van Viegen, Athena Akrami, Kate Bonnen, Eric DeWitt, Alexandre Hyafil, Helena Ledmyr, Grace W. Lindsay, Patrick Mineault, John D. Murray, Xaq Pitkow, Aina Puce, Madineh Sedigh-Sarvestani, Carsen Stringer, Titipat Achakulvisut, Elnaz Alikarami, Melvin Selim Atay, Eleanor Batty, Jeffrey C. Erlich, Byron V. Galbraith, Yueqi Guo, Ashley L. Juavinett, Matthew R. Krause, Songting Li, Marius Pachitariu, Elizabeth Straley, Davide Valeriani, Emma Vaughan, Maryam Vaziri-Pashkam, Michael L. Waskom, Gunnar Blohm, Konrad Kording, Paul Schrater, Brad Wyble, Sean Escola, Megan A. K. Peters
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 flipped) classrooms and on small group projects.
no code implementations • 20 Jan 2020 • Grace W. Lindsay
Convolutional neural networks (CNNs) were inspired by early findings in the study of biological vision.
no code implementations • 19 Nov 2015 • Grace W. Lindsay
Furthermore, the comparisons performed here suggest that a proposed model of biological FBA (the "feature similarity gain model") is effective in increasing performance.