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Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.

Y. Du, C. Durkan, R. Strudel, J. Tenenbaum, S. Dieleman, R. Fergus, J. Sohl-Dickstein, A. Doucet, и W. Grathwohl. ICML, том 202 из Proceedings of Machine Learning Research, стр. 8489-8510. PMLR, (2023)

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Angelika Strüdel

Vincent Robin

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Learning to combine primitive skills: A step towards versatile robotic manipulation §.R. Strudel, A. Pashevich, I. Kalevatykh, I. Laptev, J. Sivic, и C. Schmid. ICRA, стр. 4637-4643. IEEE, (2020)Learning Obstacle Representations for Neural Motion Planning.R. Strudel, R. Pinel, J. Carpentier, J. Laumond, I. Laptev, и C. Schmid. CoRL, том 155 из Proceedings of Machine Learning Research, стр. 355-364. PMLR, (2020)Imagen 3.J. Baldridge, J. Bauer, M. Bhutani, N. Brichtova, A. Bunner, K. Chan, Y. Chen, S. Dieleman, Y. Du, Z. Eaton-Rosen и 89 other автор(ы). CoRR, (2024)Assembly Planning from Observations under Physical Constraints.T. Chabal, R. Strudel, E. Arlaud, J. Ponce, и C. Schmid. IROS, стр. 10223-10229. IEEE, (2022)Learning representations for visually-guided robotics. (Apprentissage de représentations visuelles pour la robotique).R. Strudel. INRIA, Rocquencourt, France, (2023)Robust Visual Sim-to-Real Transfer for Robotic Manipulation.R. Pinel, R. Strudel, S. Chen, E. Arlaud, I. Laptev, и C. Schmid. IROS, стр. 992-999. (2023)Segmenter: Transformer for Semantic Segmentation.R. Strudel, R. Pinel, I. Laptev, и C. Schmid. ICCV, стр. 7242-7252. IEEE, (2021)Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.Y. Du, C. Durkan, R. Strudel, J. Tenenbaum, S. Dieleman, R. Fergus, J. Sohl-Dickstein, A. Doucet, и W. Grathwohl. ICML, том 202 из Proceedings of Machine Learning Research, стр. 8489-8510. PMLR, (2023)Learning to Augment Synthetic Images for Sim2Real Policy Transfer.A. Pashevich, R. Strudel, I. Kalevatykh, I. Laptev, и C. Schmid. IROS, стр. 2651-2657. IEEE, (2019)

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