A survey that refuses to stop at publication

What it does This repository is an open, continuously updated companion to the 2020 ACM Computing Surveys article “A Survey on Bayesian Deep Learning.” It organizes papers into a tidy taxonomy spanning recommender systems, healthcare, NLP, computer vision, federated learning, and more. Think of it as a curated literature index with PDF links rather than a software project.

The interesting bit The authors treat the README as a living appendix, cross-referencing papers that appear in multiple categories rather than letting the survey go stale. The centerpiece is a large taxonomy table mapping the entire BDL landscape.

Key highlights

• Extends a peer-reviewed ACM Computing Surveys (2020) paper with newer work
• Covers 15+ subfields, from domain adaptation to AI4Science
• Cross-references papers that belong to multiple categories
• Links directly to PDFs, project pages, and code repositories for listed work
• Includes the authors’ own follow-up research (e.g., Nature Medicine healthcare application)

Caveats

• It is a reading list, not a framework or codebase: there are no implementations here
• The README is long and dense; navigation relies entirely on anchor links

Verdict Researchers and graduate students hunting for Bayesian deep learning papers in a specific domain should bookmark this. If you are looking for libraries or training scripts, look elsewhere.