3 papers
stat.ML2026
Branching Flows: Discrete, Continuous, and Manifold Flow Matching with Splits and Deletions
Lukas Billera, Hedwig Nora Nordlinder, Jack Collier Ryder +4
Diffusion and flow matching approaches to generative modeling have shown promise in domains where the state space is continuous, such as image generation or protein folding & desig…
cs.LG2026
Latent Process Generator Matching
Lukas Billera, Hedwig Nora Nordlinder, Ben Murrell
Many recent flow-matching and diffusion-style generative models rely on auxiliary stochastic dynamics during training: a richer process is simulated to define conditional targets,…
stat.ML2025
Time dependent loss reweighting for flow matching and diffusion models is theoretically justified
Lukas Billera, Hedwig Nora Nordlinder, Ben Murrell
This brief note clarifies that, in Generator Matching (which subsumes a large family of flow matching and diffusion models over continuous, manifold, and discrete spaces), both the…