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End-to-End Differentiable Physics for Learning and Control., , , , и . NeurIPS, стр. 7178-7189. (2018)Generalizing physical prediction by composing forces and objects., , , и . CogSci, cognitivesciencesociety.org, (2022)Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract., , , и . IJCAI, стр. 6231-6235. ijcai.org, (2019)Learning constraint-based planning models from demonstrations., , , и . IROS, стр. 5410-5416. IEEE, (2020)Graph network simulators can learn discontinuous, rigid contact dynamics., , , , , , и . CoRL, том 205 из Proceedings of Machine Learning Research, стр. 1157-1167. PMLR, (2022)Few-Shot Bayesian Imitation Learning with Logical Program Policies., , , , и . AAAI, стр. 10251-10258. AAAI Press, (2020)Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure., , и . EMNLP, стр. 1169-1180. ACL, (2014)"Just In Time" Representations for Mental Simulation in Intuitive Physics., , , , и . CogSci, cognitivesciencesociety.org, (2023)Rapid Trial-and-Error Learning in Physical Problem Solving., , и . CogSci, стр. 90. cognitivesciencesociety.org, (2019)Discovering a symbolic planning language from continuous experience., , , и . CogSci, стр. 2193. cognitivesciencesociety.org, (2019)