Relational inductive biases, deep learning, and graph networks PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ... arXiv preprint arXiv:1806.01261, 2018 | 3714 | 2018 |
Meta-Learning with Memory-Augmented Neural Networks A Santoro, S Bartunov, M Botvinick, D Wierstra, T Lillicrap Proceedings of The 33rd International Conference on Machine Learning, 1842-1850, 2016 | 3016 | 2016 |
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, 4967-4976, 2017 | 1859 | 2017 |
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 863 | 2022 |
Backpropagation and the brain TP Lillicrap, A Santoro, L Marris, CJ Akerman, G Hinton Nature Reviews Neuroscience, 1-12, 2020 | 835 | 2020 |
Deep reinforcement learning with relational inductive biases V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ... International Conference on Learning Representations, 2018 | 484* | 2018 |
Measuring abstract reasoning in neural networks A Santoro, F Hill, D Barrett, A Morcos, T Lillicrap International Conference on Machine Learning, 4477-4486, 2018 | 349* | 2018 |
Assessing the scalability of biologically-motivated deep learning algorithms and architectures S Bartunov, A Santoro, BA Richards, GE Hinton, T Lillicrap | 283 | 2018 |
Relational recurrent neural networks A Santoro, R Faulkner, D Raposo, J Rae, M Chrzanowski, T Weber, ... Advances in Neural Information Processing Systems, 7299-7310, 2018 | 264 | 2018 |
Hyperbolic Attention Networks C Gulcehre, M Denil, M Malinowski, A Razavi, R Pascanu, KM Hermann, ... arXiv preprint arXiv:1805.09786, 2018 | 260 | 2018 |
Structural foundations of optogenetics: Determinants of channelrhodopsin ion selectivity A Berndt, SY Lee, J Wietek, C Ramakrishnan, EE Steinberg, AJ Rashid, ... Proceedings of the National Academy of Sciences 113 (4), 822-829, 2016 | 254 | 2016 |
Cognitive psychology for deep neural networks: A shape bias case study S Ritter, DGT Barrett, A Santoro, MM Botvinick Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 235 | 2017 |
Data Distributional Properties Drive Emergent Few-Shot Learning in Transformers SCY Chan, A Santoro, AK Lampinen, JX Wang, A Singh, PH Richemond, ... arXiv preprint arXiv:2205.05055, 2022 | 209* | 2022 |
Unsupervised Predictive Memory in a Goal-Directed Agent G Wayne, CC Hung, D Amos, M Mirza, A Ahuja, A Grabska-Barwinska, ... arXiv preprint arXiv:1803.10760, 2018 | 199 | 2018 |
Backpropagation through time and the brain TP Lillicrap, A Santoro Current Opinion in Neurobiology 55, 82-89, 2019 | 169 | 2019 |
Patterns across multiple memories are identified over time BA Richards, F Xia, A Santoro, J Husse, MA Woodin, SA Josselyn, ... Nature neuroscience 17 (7), 981-986, 2014 | 164 | 2014 |
Environmental drivers of systematicity and generalization in a situated agent F Hill, A Lampinen, R Schneider, S Clark, M Botvinick, JL McClelland, ... International Conference on Learning Representations, 2019 | 127* | 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 | 126 | 2017 |
Reassessing pattern separation in the dentate gyrus A Santoro Frontiers in behavioral neuroscience 7, 96, 2013 | 125 | 2013 |
Learning visual question answering by bootstrapping hard attention M Malinowski, C Doersch, A Santoro, P Battaglia Proceedings of the European Conference on Computer Vision (ECCV), 3-20, 2018 | 119 | 2018 |