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 | 1877 | 2017 |
On the importance of single directions for generalization AS Morcos, DGT Barrett, NC Rabinowitz, M Botvinick arXiv preprint arXiv:1803.06959, 2018 | 357 | 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 | 356* | 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 | 236 | 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 | 192 | 2021 |
Implicit gradient regularization DGT Barrett, B Dherin arXiv preprint arXiv:2009.11162, 2020 | 139 | 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 | 132 | 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 | 127 | 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 | 92 | 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 | 73 | 2020 |
Learning optimal spike-based representations R Bourdoukan, DGT Barrett, C Machens, S Deneve Advances in Neural Information Processing Systems 25, 2294-2302, 2012 | 71 | 2012 |
Optimal compensation for neuron loss DGT Barrett, S Deneve, CK Machens Elife 5, e12454, 2016 | 60 | 2016 |
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 | 49* | 2017 |
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 | 48* | 2018 |
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 | 33 | 2024 |
Firing rate predictions in optimal balanced networks DG Barrett, S Denève, CK Machens Advances in Neural Information Processing Systems 26, 2013 | 25 | 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 | 22 | 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 | 21 | 2008 |
Discretization drift in two-player games MC Rosca, Y Wu, B Dherin, D Barrett International Conference on Machine Learning, 9064-9074, 2021 | 13 | 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 | 11 | 2009 |