Robust Neural Posterior Estimation and Statistical Model Criticism. - Daniel Ward; Patrick Cannon; Mark Beaumont; Matteo Fasiolo; Sebastian M. Schmon (NeurIPS, 2022)

Variational Gradient Descent using Local Linear Models. - Song Liu; Jack Simons; Mingxuan Yi; Mark Beaumont (CoRR, 2023)

Minimizing f-Divergences by Interpolating Velocity Fields. - Song Liu; Jiahao Yu; Jack Simons; Mingxuan Yi; Mark Beaumont (ICML, 2024)

Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models. - Louis Sharrock; Jack Simons; Song Liu; Mark Beaumont (ICML, 2024)

SoftCVI: Contrastive variational inference with self-generated soft labels. - Daniel Ward; Mark Beaumont; Matteo Fasiolo (ICLR, 2025)

Direct Fisher Score Estimation for Likelihood Maximization. - Sherman Khoo; Yakun Wang; Song Liu; Mark Beaumont (CoRR, 2025)