1 code implementation • NeurIPS 2023 • Kyle Hsu, Will Dorrell, James C. R. Whittington, Jiajun Wu, Chelsea Finn
In this work, we construct an inductive bias towards encoding to and decoding from an organized latent space.
1 code implementation • 30 Sep 2022 • William Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington
We suggest the brain must represent this consistent meaning of actions across space, as it allows you to find new short-cuts and navigate in unfamiliar settings.
no code implementations • 30 Sep 2022 • James C. R. Whittington, Will Dorrell, Surya Ganguli, Timothy E. J. Behrens
Neurons in the brain are often finely tuned for specific task variables.
no code implementations • 3 Feb 2022 • James C. R. Whittington, David McCaffary, Jacob J. W. Bakermans, Timothy E. J. Behrens
Learning and interpreting the structure of the environment is an innate feature of biological systems, and is integral to guiding flexible behaviours for evolutionary viability.
no code implementations • ICLR 2022 • James C. R. Whittington, Joseph Warren, Timothy E. J. Behrens
Many deep neural network architectures loosely based on brain networks have recently been shown to replicate neural firing patterns observed in the brain.
no code implementations • 23 Jul 2021 • James C. R. Whittington, Rishabh Kabra, Loic Matthey, Christopher P. Burgess, Alexander Lerchner
Learning structured representations of visual scenes is currently a major bottleneck to bridging perception with reasoning.
no code implementations • NeurIPS 2018 • James C. R. Whittington, Timothy H. Muller, Shirley Mark, Caswell Barry, Timothy E. J. Behrens
We propose that to generalise structural knowledge, the representations of the structure of the world, i. e. how entities in the world relate to each other, need to be separated from representations of the entities themselves.