The Geometry Behind Diffusion and Flow Matching: Gradient Flows and Geodesics in

arXiv:2607.06646v1 Announce Type: cross Abstract: This paper introduces Diffusion Semi-Relaxed Fused Gromov-Wasserstein (DsrFGW), a novel method for graph comparison that unifies

arXiv:2603.22309v1 Announce Type: cross Abstract: Partial differential equation (PDE) simulation holds extensive significance in scientific research. Currently, the integration of

<!-- SC_OFF --><div class="md"><p>Peter Holderrieth and Ezra Erives just released their new MIT 2026 course on flow matching and diffusion models! It introduces the full stack of

arXiv:2605.00007v1 Announce Type: cross Abstract: Independent sample generation is the prevailing paradigm in modern diffusion-based generative models of AI. We ask a different

arXiv:2610.02260v1 Announce Type: new Abstract: Flow matching models excel at generative modeling, and many downstream applications require their samples to satisfy prescribed