Tips and tricks for analyzing and presenting machine learning results
These lecture notes summarize the main points from the third tutorial session of the workshop “DANGER: Data, Numbers, and Geometry” held in April 2026 at the Banff International Research Station for Mathematical Innovation and Discovery (BIRS). The accompanying code and slide presentation can be found at jnhoward/Banff-Tutorial/ .
Authors
- J. Howard (ORCID: https://orcid.org/0000-0001-8295-7727)
Institutions
- University of California, Santa Barbara (US)
- Kavli Institute for Particle Astrophysics and Cosmology (US)
- Kavli Institute for Theoretical Physics (US)
Publication Details
- Journal
- AI in Mathematics and Theoretical Physics
- Published
- 2026-09-25
- DOI
- https://doi.org/10.1142/s3082883x26400047
- Primary Topic
- Gaussian Processes and Bayesian Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00