arXiv Machine Learning
Jun 16

Amortized mean-shift interacting particles

arXiv:2606. 15871v1 Announce Type: cross Abstract: Bayesian inference for inverse problems is run to evaluate integrals -- posterior expectations, tail probabilities, and risks -- across a stream of observations.

By Ali Siahkoohi
arXiv AI
Jul 20

Energy-based Transport for Amortized Bayesian Inference

arXiv:2605. 15407v3 Announce Type: replace-cross Abstract: We consider amortized Bayesian inference for nonlinear inverse problems using only samples from the joint distribution of parameters and observations, including problems with unknown functions in a Banach space.

By Ricardo Baptista, Hojjat Kaveh, Andrew M. Stuart
arXiv Machine Learning
Sep 17

Bayesian Quadrature

This survey article reviews Bayesian quadrature, a probabilistic, model‑based method for numerical integration and expectation estimation. It provides a systematic taxonomy of Bayesian quadrature techniques across modelling, inference, and sampling, presents theoretical guarantees, and includes a controlled numerical study illustrating the impact of different methodological choices. The paper also discusses practical challenges, limitations, and offers an extensive bibliography covering machine learning, statistics, mathematics, and engineering applications.

By Maren Mahsereci, Toni Karvonen