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Simulation of Conditioned Diffusions on the Flat Torus.

, , и . GSI, том 11712 из Lecture Notes in Computer Science, стр. 685-694. Springer, (2019)

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Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 2368-2377. PMLR, (2019)Wrapped Gaussian Process Regression on Riemannian Manifolds., и . CVPR, стр. 5580-5588. Computer Vision Foundation / IEEE Computer Society, (2018)Bayesian Inference for Optimal Transport with Stochastic Cost., , и . ACML, том 157 из Proceedings of Machine Learning Research, стр. 1601-1616. PMLR, (2021)Affine Transport for Sim-to-Real Domain Adaptation., , , , и . CoRR, (2021)Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes., и . NIPS, стр. 5660-5670. (2017)Simulation of Conditioned Diffusions on the Flat Torus., , и . GSI, том 11712 из Lecture Notes in Computer Science, стр. 685-694. Springer, (2019)Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models., , и . CoRR, (2018)How Well Do WGANs Estimate the Wasserstein Metric?, , и . CoRR, (2019)Understanding deep neural networks through the lens of their non-linearity., , , , , , , , и . CoRR, (2023)Bayesian Inference for Optimal Transport with Stochastic Cost., , и . CoRR, (2020)