Kelsey Allen
Kelsey Allen
Research Scientist, DeepMind
Verified email at
Cited by
Cited by
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
Search for high-mass dilepton resonances in collisions at with the ATLAS detector
G Aad, B Abbott, J Abdallah, S Abdel Khalek, O Abdinov, R Aben, B Abi, ...
Physical Review D 90 (5), 052005, 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
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
Infinite mixture prototypes for few-shot learning
K Allen, E Shelhamer, H Shin, J Tenenbaum
International conference on machine learning, 232-241, 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
Residual policy learning
T Silver, K Allen, J Tenenbaum, L Kaelbling
arXiv preprint arXiv:1812.06298, 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
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
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
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
Physical design using differentiable learned simulators
KR Allen, T Lopez-Guevara, K Stachenfeld, A Sanchez-Gonzalez, ...
arXiv preprint arXiv:2202.00728, 2022
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
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
Learning rigid dynamics with face interaction graph networks
KR Allen, Y Rubanova, T Lopez-Guevara, W Whitney, ...
arXiv preprint arXiv:2212.03574, 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
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
Using games to understand the mind
K Allen, F Brändle, M Botvinick, JE Fan, SJ Gershman, A Gopnik, ...
Nature Human Behaviour, 1-9, 2024
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
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
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