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SE(3) diffusion model with application to protein backbone generation.

, , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 40001-40039. PMLR, (2023)

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LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 6315-6324. PMLR, (2019)The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 141-150. PMLR, (2019)SE(3) diffusion model with application to protein backbone generation., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 40001-40039. PMLR, (2023)Many processors, little time: MCMC for partitions via optimal transport couplings., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 3483-3514. PMLR, (2022)Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem., , , , , , and . CoRR, (2022)Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem., , , , , , and . ICLR, OpenReview.net, (2023)For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets., , and . NeurIPS, page 13471-13484. (2021)Gaussian processes at the Helm(holtz): A more fluid model for ocean currents., , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 2113-2163. PMLR, (2023)