Abstract: A Pruned Bayesian Neural Network (PBNN) algorithm based on the collaborative optimization of variational inference and network pruning is proposed in this paper. It aims to address the ...

Abstract: Bayesian networks are widely used for causal discovery and probabilistic modeling across diverse domains including healthcare, multi-dimensional data analysis, environmental modeling, and ...

ABSTRACT: The present study aimed to examine the impact of emotion regulation on depression symptoms, with a particular focus on the mediating roles of social anxiety and loneliness among Chinese ...

Metabolic syndrome is a cluster of conditions that occur together, increasing the risk of heart disease, stroke, and type 2 diabetes. This project uses an explorative approach with Bayesian networks ...

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...

Introduction: During the commissioning and operation of shale gas pipelines, multiple perforation accidents caused by internal corrosion have occurred. Research on internal corrosion probability ...

Landslide susceptibility assessment is crucial to mitigate the severe impacts of landslides. Although Bayesian network (BN) has been widely used in landslide susceptibility assessment, no study has ...

Repository for the code of the "Introduction to Machine Learning" (IML) lecture at the "Learning & Adaptive Systems Group" at ETH Zurich.