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Riemannian Flow Matching on General Geometries., and . CoRR, (2023)Matching Normalizing Flows and Probability Paths on Manifolds., , , , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 1749-1763. PMLR, (2022)Neural Spatio-Temporal Point Processes., , and . ICLR, OpenReview.net, (2021)Neural Conservation Laws: A Divergence-Free Perspective., , and . NeurIPS, (2022)SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models, , , , , , and . International Conference on Learning Representations, (2020)Scalable Gradients for Stochastic Differential Equations., , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 3870-3882. PMLR, (2020)FlowMM: Generating Materials with Riemannian Flow Matching., , , and . ICML, OpenReview.net, (2024)Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control., , , and . CoRR, (2024)Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization., , , and . CoRR, (2020)Neural Ordinary Differential Equations, , , and . (2018)cite arxiv:1806.07366.