Quantum machine learning (QML) is an emerging research field that deals with quantum algorithms for data analysis. It is hoped that QML will yield practical demonstrations of quantum advantage by ...

Abstract: In this work, we have developed a variational Bayesian inference theory of elasticity, which is accomplished by using a mixed Variational Bayesian inference Finite Element Method (VBI-FEM) ...

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...

What is this book about? Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that ...

Code to reproduce results in Ziyi Yin*, Rafael Orozco*, Mathias Louboutin, Felix J. Herrmann, "WISE: full-Waveform variational Inference via Subsurface Extensions". Published in Geophysics. DOI: ...

Variational inference (VI) seeks to approximate a target distribution \(\pi\) by an element of a tractable family of distributions. Of key interest in statistics and machine learning is Gaussian VI, ...