GitHub

Stacking Variational Bayesian Monte Carlo (S-VBMC)

Stacking Variational Bayesian Monte Carlo (S-VBMC)[1] is a fast post-processing step for Variational Bayesian Monte Carlo (VBMC). VBMC is an approximate Bayesian inference technique that produces a ...
GitHub

Kalman and Bayesian Filters in Python

Kalman and Bayesian Filters in Python Introductory text for Kalman and Bayesian filters. All code is written in Python, and the book itself is written using Jupyter Notebook so that you can run and ...
IEEE

Scalable Quantum Approximate Optimisation with Adaptive Bayesian Dimensionality Reduction

Abstract: Quantum Approximate Optimisation Algorithm (QAOA) has emerged as a promising hybrid quantum-classical approach for tackling NP-hard combinatorial optimisation problems by combining quantum ...
IEEE

Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent

Abstract: A crucial task in predictive maintenance is estimating the remaining useful life of physical systems. In the last decade, deep learning has improved considerably upon traditional model-based ...
Nature

Computational science articles from across Nature Portfolio

Computational science is a discipline concerned with the design, implementation and use of mathematical models to analyse and solve scientific problems. Typically, the term refers to the use of ...