Search Results for author: Mark Beaumont

Found 4 papers, 2 papers with code

Minimizing $f$-Divergences by Interpolating Velocity Fields

1 code implementation24 May 2023 Song Liu, Jiahao Yu, Jack Simons, Mingxuan Yi, Mark Beaumont

Wasserstein Gradient Flow can move particles along a path that minimizes the $f$-divergence between the target and particle distributions.

Domain Adaptation Imputation

Robust Neural Posterior Estimation and Statistical Model Criticism

no code implementations12 Oct 2022 Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M Schmon

In this work we revisit neural posterior estimation (NPE), a class of algorithms that enable black-box parameter inference in simulation models, and consider the implication of a simulation-to-reality gap.

Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models

1 code implementation10 Oct 2022 Louis Sharrock, Jack Simons, Song Liu, Mark Beaumont

We embed the model into a sequential training procedure, which guides simulations using the current approximation of the posterior at the observation of interest, thereby reducing the simulation cost.

Bayesian Inference

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