Tom Silver
Cited by
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Schema networks: Zero-shot transfer with a generative causal model of intuitive physics
K Kansky, T Silver, DA Mély, M Eldawy, M Lázaro-Gredilla, X Lou, ...
International Conference on Machine Learning, 1809-1818, 2017
Residual policy learning
T Silver, K Allen, J Tenenbaum, L Kaelbling
arXiv preprint arXiv:1812.06298, 2018
Transforming clinical data into actionable prognosis models: machine-learning framework and field-deployable app to predict outcome of Ebola patients
A Colubri, T Silver, T Fradet, K Retzepi, B Fry, P Sabeti
PLoS neglected tropical diseases 10 (3), e0004549, 2016
Behavior is everything: Towards representing concepts with sensorimotor contingencies
N Hay, M Stark, A Schlegel, C Wendelken, D Park, E Purdy, T Silver, ...
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
Learning sparse relational transition models
V Xia, W Zi, K Allen, T Silver, LP Kaelbling
International Conference on Learning Representations (ICLR), 2019
Integrated task and motion planning
CR Garrett, R Chitnis, R Holladay, B Kim, T Silver, LP Kaelbling, ...
arXiv preprint arXiv:2010.01083, 2020
Few-Shot Bayesian Imitation Learning with Logical Program Policies
T Silver, KR Allen, AK Lew, L Kaelbling, J Tenenbaum
Thirty-Fourth AAAI Conference on Artificial Intelligence, 0
Online bayesian goal inference for boundedly-rational planning agents
T Zhi-Xuan, JL Mann, T Silver, JB Tenenbaum, VK Mansinghka
arXiv preprint arXiv:2006.07532, 2020
PDDLGym: Gym environments from PDDL problems
T Silver, R Chitnis
arXiv preprint arXiv:2002.06432, 2020
Glib: Efficient exploration for relational model-based reinforcement learning via goal-literal babbling
R Chitnis, T Silver, J Tenenbaum, LP Kaelbling, T Lozano-Pérez
Proc. AAAI, 2021
Planning with learned object importance in large problem instances using graph neural networks
T Silver, R Chitnis, A Curtis, J Tenenbaum, T Lozano-Perez, LP Kaelbling
arXiv preprint arXiv:2009.05613, 2020
Learning Symbolic Operators for Task and Motion Planning
T Silver, R Chitnis, J Tenenbaum, LP Kaelbling, T Lozano-Perez
arXiv preprint arXiv:2103.00589, 2021
CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs
R Chitnis, T Silver, B Kim, LP Kaelbling, T Lozano-Perez
arXiv preprint arXiv:2007.13202, 2020
Discovering a symbolic planning language from continuous experience.
J Loula, T Silver, KR Allen, J Tenenbaum
CogSci, 2193, 2019
Learning constraint-based planning models from demonstrations
J Loula, K Allen, T Silver, J Tenenbaum
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