IEEE

Matrix-Inversion-Free Sparse Bayesian Learning for High-Resolution Radar Imagery via Improved Variational Inference

Abstract: Sparse Bayesian learning (SBL) is an advanced statistical framework that dominantly enhances the sparse features of targets of interest in radar imagery. A widely adopted strategy for ...
Morningstar

Professor Sarfaraz Niazi's Scientific Framework Adopted as FDA Modernizes Clinical Trial Evaluation Through Bayesian Methods

WASHINGTON, Jan. 20, 2026 /PRNewswire/ -- The U.S. Food and Drug Administration (FDA) has issued new draft guidance modernizing statistical methodologies used in clinical trials, formally recognizing ...
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 Two-Phase Adaptive Prior Kalman Filter With Unknown Noise Covariances

Abstract: This paper addresses the issue of online state estimation when the covariances of the process and measurement noise (PMN) are unknown. In practical scenarios, inaccurate PMN covariances lead ...
GitHub

Black-Box Variational Inference on Bayesian Neural Networks

These instructions will allow you to run this project on your local machine. Figure 1: Variational loss function and its gradient with 1 MC sample Figure 2: Variational loss function and its gradient ...