David G.T. Barrett
David G.T. Barrett
Google DeepMind and St Johns College, Cambridge
Verified email at
Cited by
Cited by
A simple neural network module for relational reasoning
A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ...
Advances in neural information processing systems 30, 2017
On the importance of single directions for generalization
AS Morcos, DGT Barrett, NC Rabinowitz, M Botvinick
arXiv preprint arXiv:1803.06959, 2018
Measuring abstract reasoning in neural networks
D Barrett, F Hill, A Santoro, A Morcos, T Lillicrap
International Conference on Machine Learning, 4477-4486, 2018
Cognitive psychology for deep neural networks: A shape bias case study
S Ritter, DGT Barrett, A Santoro, MM Botvinick
International conference on machine learning, 2940-2949, 2017
On the origin of implicit regularization in stochastic gradient descent
SL Smith, B Dherin, DGT Barrett, S De
arXiv preprint arXiv:2101.12176, 2021
Implicit gradient regularization
DGT Barrett, B Dherin
arXiv preprint arXiv:2009.11162, 2020
Analyzing biological and artificial neural networks: challenges with opportunities for synergy?
DGT Barrett, AS Morcos, JH Macke
Current opinion in neurobiology 55, 55-64, 2019
Discovering objects and their relations from entangled scene representations
D Raposo, A Santoro, D Barrett, R Pascanu, T Lillicrap, P Battaglia
arXiv preprint arXiv:1702.05068, 2017
Learning to make analogies by contrasting abstract relational structure
F Hill, A Santoro, DGT Barrett, AS Morcos, T Lillicrap
arXiv preprint arXiv:1902.00120, 2019
An explicitly relational neural network architecture
M Shanahan, K Nikiforou, A Creswell, C Kaplanis, D Barrett, M Garnelo
International Conference on Machine Learning, 8593-8603, 2020
Learning optimal spike-based representations
R Bourdoukan, DGT Barrett, C Machens, S Deneve
Advances in Neural Information Processing Systems 25, 2294-2302, 2012
Optimal compensation for neuron loss
DGT Barrett, S Deneve, CK Machens
Elife 5, e12454, 2016
Spectral inference networks: Unifying spectral methods with deep learning
D Pfau, S Petersen, A Agarwal, D Barrett, K Stachenfeld
arXiv preprint arXiv:1806.02215 2, 2018
Building machines that learn and think for themselves
M Botvinick, DGT Barrett, P Battaglia, N de Freitas, D Kumaran, JZ Leibo, ...
Behavioral and Brain Sciences 40, 2017
Capabilities of gemini models in medicine
K Saab, T Tu, WH Weng, R Tanno, D Stutz, E Wulczyn, F Zhang, ...
arXiv preprint arXiv:2404.18416, 2024
Firing rate predictions in optimal balanced networks
DG Barrett, S Denève, CK Machens
Advances in Neural Information Processing Systems 26, 2013
Why neural networks find simple solutions: The many regularizers of geometric complexity
B Dherin, M Munn, M Rosca, D Barrett
Advances in Neural Information Processing Systems 35, 2333-2349, 2022
Taking plateau into microgravity: The formation of an eightfold vertex in a system of soap films
DGT Barrett, S Kelly, EJ Daly, MJ Dolan, W Drenckhan, D Weaire, ...
Microgravity-Science and Technology 20, 17-22, 2008
Discretization drift in two-player games
MC Rosca, Y Wu, B Dherin, D Barrett
International Conference on Machine Learning, 9064-9074, 2021
Sparse coding of birdsong and receptive field structure in songbirds
G Greene, DGT Barrett, K Sen, C Houghton
Network: Computation in neural systems 20 (3), 162-177, 2009
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