IEEE

Bayesian Convolutional Neural Networks for Prior Learning in Graph Signal Recovery

Abstract: Graph signal recovery (GSR) is a fundamental problem in graph signal processing, where the objective is to reconstruct a complete signal defined over a graph from a subset of noisy or ...
IEEE

Bayesian Graph Convolutional Neural Network with Noise Injection

Abstract: Graph neural networks (GNNs) have achieved significant success in a variety of graph-related tasks, such as node classification, link prediction, and graph classification. However, GNNs ...
CU Boulder News & Events

DTSA 5726: Introduction to Bayesian Statistics for Data Science Applications

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...
GitHub

Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective

This repository implements Sequential Flow Matching for the paper Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective (https://arxiv.org/abs/2602. ...
lse

Bayesian Machine Learning

This course is available on the MSc in Applied Social Data Science, MSc in Data Science, MSc in Econometrics and Mathematical Economics, MSc in Health Data Science, MSc in Operations Research & ...