Cartan flow matching
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Abstract (arXiv)
We introduce Cartan flow matching, a general framework for training flow matching models on Riemannian symmetric spaces, i.e. Riemannian manifolds with the property that at any point there exists a geodesic symmetry. This is a large class of manifolds that includes the sphere, hyperbolic space and Grassmannians. We exploit their algebraic structure to reformulate flow matching on symmetric spaces as flow matching on a subspace of the Lie algebra of their isometry group, thus linearizing the problem and avoiding the need to construct geodesic interpolation paths on the manifold. As an application, we showcase our framework on the real Grassmannians operatornameSO(n) / operatornameSO(k) × operatornameSO(n-k) .
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References · 23
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
- 2022Flow Matching for Generative Modelingcited by 5,426
- 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
- 2018Neural Ordinary Differential Equationscited by 3,733
- 2022Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flowcited by 3,550
- 2022Building Normalizing Flows with Stochastic Interpolantscited by 964
- 2023Improving and generalizing flow-based generative models with minibatch optimal transportcited by 835
- 2023Flow Matching on General Geometriescited by 260
- 2020Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densitiescited by 248
- 2021E(n) Equivariant Normalizing Flowscited by 165
- 2020Riemannian Continuous Normalizing Flowscited by 143
11 more
- 2023Equivariant flow matchingcited by 131
- 2022Riemannian Diffusion Modelscited by 120
- 2020Normalizing Flows on Tori and Spherescited by 117
- 2020Neural Manifold Ordinary Differential Equationscited by 81
- 2024Variational Flow Matching for Graph Generationcited by 78
- 2016Normalizing Flows on Riemannian Manifoldscited by 68
- 2021Moser Flow: Divergence-based Generative Modeling on Manifoldscited by 67
- 2022Matching Normalizing Flows and Probability Paths on Manifoldscited by 57
- 2020Latent Variable Modelling with Hyperbolic Normalizing Flowscited by 49
- 2021Continuous normalizing flows on manifoldscited by 10
- 2025Flow Matching on Lie Groupscited by 4
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- 2026Flow matching on homogeneous spaces
- 2026Total Variation Rates for Riemannian Flow Matching
- 2025Riemannian Variational Flow Matching for Material and Protein Design
- 2025Energy Guided Geometric Flow Matching
- 2025Graph Generation with Spectral Geodesic Flow Matching
- 2025Efficient Diffusion Models for Symmetric Manifolds
- 2026Manifold-Stable Flow Matching
- 2026Probabilistic Geodesic Flow Matching on Location-Scale Families