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Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning.

, , , and . Robotics: Science and Systems, (2018)

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End-to-End Differentiable Physics for Learning and Control., , , , and . NeurIPS, page 7178-7189. (2018)Generalizing physical prediction by composing forces and objects., , , and . CogSci, cognitivesciencesociety.org, (2022)Infinite Mixture Prototypes for Few-shot Learning., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 232-241. PMLR, (2019)Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning., , , and . Robotics: Science and Systems, (2018)Simulation and heuristics in flexible tool use., , and . CogSci, cognitivesciencesociety.org, (2017)Learning rigid-body simulators over implicit shapes for large-scale scenes and vision., , , , , and . CoRR, (2024)Combining rules and simulation to explain infant physical learning., , and . CogSci, cognitivesciencesociety.org, (2021)Learning constraint-based planning models from demonstrations., , , and . IROS, page 5410-5416. IEEE, (2020)Graph network simulators can learn discontinuous, rigid contact dynamics., , , , , , and . CoRL, volume 205 of Proceedings of Machine Learning Research, page 1157-1167. PMLR, (2022)Few-Shot Bayesian Imitation Learning with Logical Program Policies., , , , and . AAAI, page 10251-10258. AAAI Press, (2020)