Which priors matter? Benchmarking models for learning latent dynamics. - Aleksandar Botev; Andrew Jaegle; Peter Wirnsberger; Daniel Hennes; Irina Higgins (NeurIPS Datasets and Benchmarks, 2021)

SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision. - Irina Higgins; Peter Wirnsberger; Andrew Jaegle; Aleksandar Botev (NeurIPS, 2021)

MultiScale MeshGraphNets. - Meire Fortunato; Tobias Pfaff; Peter Wirnsberger; Alexander Pritzel; Peter W. Battaglia (CoRR, 2022)

GraphCast: Learning skillful medium-range global weather forecasting. - Rémi Lam; Alvaro Sanchez-Gonzalez; Matthew Willson; Peter Wirnsberger; Meire Fortunato; Alexander Pritzel; Suman V. Ravuri; Timo Ewalds; Ferran Alet; Zach Eaton-Rosen; Weihua Hu; Alexander Merose; et al. (CoRR, 2022)

Normalizing flows for atomic solids. - Peter Wirnsberger; George Papamakarios; Borja Ibarz; Sébastien Racanière; Andrew J. Ballard; Alexander Pritzel; Charles Blundell (Mach. Learn. Sci. Technol., 2022)

Gibbs free energies via isobaric-isothermal flows. - Peter Wirnsberger; Borja Ibarz; George Papamakarios (CoRR, 2023)

Estimating Gibbs free energies via isobaric-isothermal flows. - Peter Wirnsberger; Borja Ibarz; George Papamakarios (Mach. Learn. Sci. Technol., 2023)

Target Score Matching. - Valentin De Bortoli; Michael J. Hutchinson; Peter Wirnsberger; Arnaud Doucet (CoRR, 2024)