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Simulation of Conditioned Diffusions on the Flat Torus.

, , and . GSI, volume 11712 of Lecture Notes in Computer Science, page 685-694. Springer, (2019)

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Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 2368-2377. PMLR, (2019)Affine Transport for Sim-to-Real Domain Adaptation., , , , and . CoRR, (2021)Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes., and . NIPS, page 5660-5670. (2017)Wrapped Gaussian Process Regression on Riemannian Manifolds., and . CVPR, page 5580-5588. Computer Vision Foundation / IEEE Computer Society, (2018)Bayesian Inference for Optimal Transport with Stochastic Cost., , and . ACML, volume 157 of Proceedings of Machine Learning Research, page 1601-1616. PMLR, (2021)Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models., , and . CoRR, (2018)Simulation of Conditioned Diffusions on the Flat Torus., , and . GSI, volume 11712 of Lecture Notes in Computer Science, page 685-694. Springer, (2019)How Well Do WGANs Estimate the Wasserstein Metric?, , and . CoRR, (2019)Understanding deep neural networks through the lens of their non-linearity., , , , , , , , and . CoRR, (2023)A Formalization of the Natural Gradient Method for General Similarity Measures., , and . GSI, volume 11712 of Lecture Notes in Computer Science, page 599-607. Springer, (2019)