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Scalable Gradients for Stochastic Differential Equations.

, , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3870-3882. PMLR, (2020)

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Statistical manifolds from optimal transport. (2017)cite arxiv:1712.03610Comment: 28 pages.Logarithmic Divergences: Geometry and Interpretation of Curvature., and . GSI, volume 11712 of Lecture Notes in Computer Science, page 413-422. Springer, (2019)Information Geometry for the Working Information Theorist., , and . CoRR, (2023)Tsallis and Rényi deformations linked via a new λ-duality., and . CoRR, (2021)Scalable Gradients for Stochastic Differential Equations., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3870-3882. PMLR, (2020)Optimization of relative arbitrage. (2014)cite arxiv:1407.8300Comment: 32 pages, 5 figures, 2 tables.Projections with Logarithmic Divergences., and . GSI, volume 12829 of Lecture Notes in Computer Science, page 477-486. Springer, (2021)Scalable Gradients and Variational Inference for Stochastic Differential Equations., , , and . AABI, volume 118 of Proceedings of Machine Learning Research, page 1-28. PMLR, (2019)