Equivariant Conditional Neural Processes. - Peter Holderrieth; Michael J. Hutchinson; Yee Whye Teh (CoRR, 2020)

Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes. - Peter Holderrieth; Michael J. Hutchinson; Yee Whye Teh (ICML, 2021)

Hamiltonian Score Matching and Generative Flows. - Peter Holderrieth; Yilun Xu; Tommi S. Jaakkola (NeurIPS, 2024)

Flow Matching Guide and Code. - Yaron Lipman; Marton Havasi; Peter Holderrieth; Neta Shaul; Matt Le 001; Brian Karrer; Ricky T. Q. Chen; David Lopez-Paz; Heli Ben-Hamu; Itai Gat (CoRR, 2024)

Generator Matching: Generative modeling with arbitrary Markov processes. - Peter Holderrieth; Marton Havasi; Jason Yim; Neta Shaul; Itai Gat; Tommi S. Jaakkola; Brian Karrer; Ricky T. Q. Chen; Yaron Lipman (ICLR, 2025)

Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective. - Neta Shaul; Itai Gat; Marton Havasi; Daniel Severo 001; Anuroop Sriram; Peter Holderrieth; Brian Karrer; Yaron Lipman; Ricky T. Q. Chen (ICLR, 2025)

LEAPS: A discrete neural sampler via locally equivariant networks. - Peter Holderrieth; Michael S. Albergo; Tommi S. Jaakkola (CoRR, 2025)

An Introduction to Flow Matching and Diffusion Models. - Peter Holderrieth; Ezra Erives (CoRR, 2025)