IEEE

Image-to-Image Bayesian Flow Networks With Structurally Informative Priors

Abstract: Generative models represented by diffusion models have recently shown great potential in image generation. They usually use a reverse iteration process to map noise into the data. However, ...
IEEE

Probabilistic Modeling of Train Operations for Uncertainty Quantification: A Context-Aware Bayesian Network Approach

Abstract: In this study, train operations were modeled by Bayesian networks (BN), to use the probability essence of the BN to quantify their uncertainty (e.g., the epistemic and aleatoric uncertainty ...
eLife

Extracting Value Coding Features from Individual Serotonin Neurons

The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...
BMJ

Comparative efficacy and safety of high-dose rifamycin regimens for tuberculosis treatment: a Bayesian network meta-analysis

Objectives High-dose rifamycin (HDR) regimens have demonstrated significant potential in tuberculosis (TB) treatment. This study aims to evaluate the efficacy and safety profile of different HDR ...
Security Boulevard

PyTorch tensors, neural networks and Autograd: an introduction

For Python application developers looking to harness the power of machine learning, understanding the foundational tools is critical. Among those tools is PyTorch, a leading open-source machine ...
Frontiers

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

The conflict of interest statement was erroneously given as “Authors FC, JG, NA, and EA were employed by Minutia.AI Pte. Ltd.” The correct conflict of interest statement is “Authors FC, JG and NA were ...