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

Bayesian statistical methods for genetic association studies

p-values are commonly used as summaries of evidence for association between a genetic variant and phenotype, but they have an important limitation in that they are unable to quantify how confident one ...
Investing

FDA openness to Bayesian methods noted by BioStem Technologies

POMPANO BEACH, Fla. - BioStem Technologies, Inc. (OTC:BSEM), a microcap company with a market capitalization of $90.22 million, highlighted recent statements from FDA leadership indicating greater ...
Investopedia

How to Use Bayesian Methods for Accurate Financial Forecasting

Daniel McNulty began writing for Investopedia in 2012. His work includes articles on financial analysis, asset allocation, and trading strategies. Marguerita is a Certified Financial Planner (CFP), ...
IEEE

A Variational Bayesian-Based Augmented State Joint Estimation Method for Heavy-Tailed Colored Noise

Abstract: The measurement of dynamic system is corrupted by colored noise and involved heavy-tailed characteristics simultaneously for target tracking in practice. Mostly existing work employs the the ...
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 ...