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
3909 2018 Search for high-mass dilepton resonances in G Aad, B Abbott, J Abdallah, S Abdel Khalek, O Abdinov, R Aben, B Abi, ...
Physical Review D 90 (5), 052005, 2014
790 2014 End-to-end differentiable physics for learning and control F de Avila Belbute-Peres, K Smith, K Allen, J Tenenbaum, JZ Kolter
Advances in neural information processing systems 31, 2018
464 2018 Differentiable physics and stable modes for tool-use and manipulation planning MA Toussaint, KR Allen, KA Smith, JB Tenenbaum
Robotics: Science and systems foundation, 2018
330 2018 Infinite mixture prototypes for few-shot learning K Allen, E Shelhamer, H Shin, J Tenenbaum
International conference on machine learning, 232-241, 2019
306 2019 Relational inductive biases, deep learning, and graph networks. arXiv 2018 PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
220 2018 Residual policy learning T Silver, K Allen, J Tenenbaum, L Kaelbling
arXiv preprint arXiv:1812.06298, 2018
205 2018 Relational inductive bias for physical construction in humans and machines JB Hamrick, KR Allen, V Bapst, T Zhu, KR McKee, JB Tenenbaum, ...
arXiv preprint arXiv:1806.01203, 2018
141 2018 Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning KR Allen, KA Smith, JB Tenenbaum
Proceedings of the National Academy of Sciences 117 (47), 29302-29310, 2020
135 2020 Few-shot bayesian imitation learning with logical program policies T Silver, KR Allen, AK Lew, LP Kaelbling, J Tenenbaum
Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 10251 …, 2020
52 2020 Detecting disagreement in conversations using pseudo-monologic rhetorical structure K Allen, G Carenini, R Ng
Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014
51 2014 Physical design using differentiable learned simulators KR Allen, T Lopez-Guevara, K Stachenfeld, A Sanchez-Gonzalez, ...
arXiv preprint arXiv:2202.00728, 2022
44 2022 Graph network simulators can learn discontinuous, rigid contact dynamics KR Allen, TL Guevara, Y Rubanova, K Stachenfeld, A Sanchez-Gonzalez, ...
Conference on Robot Learning, 1157-1167, 2023
42 2023 Interactions increase forager availability and activity in harvester ants E Pless, J Queirolo, N Pinter-Wollman, S Crow, K Allen, MB Mathur, ...
PloS one 10 (11), e0141971, 2015
33 2015 Learning rigid dynamics with face interaction graph networks KR Allen, Y Rubanova, T Lopez-Guevara, W Whitney, ...
arXiv preprint arXiv:2212.03574, 2022
31 2022 The tools challenge: Rapid trial-and-error learning in physical problem solving KR Allen, KA Smith, JB Tenenbaum
arXiv preprint arXiv:1907.09620 14, 2019
26 2019 Using games to understand the mind K Allen, F Brändle, M Botvinick, JE Fan, SJ Gershman, A Gopnik, ...
Nature Human Behaviour, 1-9, 2024
20 2024 Learning constraint-based planning models from demonstrations J Loula, K Allen, T Silver, J Tenenbaum
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
17 2020 Inverse design for fluid-structure interactions using graph network simulators K Allen, T Lopez-Guevara, KL Stachenfeld, A Sanchez Gonzalez, ...
Advances in Neural Information Processing Systems 35, 13759-13774, 2022
13 2022 Ogre: An object-based generalization for reasoning environment KR Allen, A Bakhtin, K Smith, JB Tenenbaum, L van der Maaten
NeurIPS Workshop on Object Representations for Learning and Reasoning, 2020
10 2020 
Joshua B. TenenbaumMITEmail verificata su mit.edu