Resources for Gaussian processes and Bayesian optimization

Gaussian Processes

• Gortler et al. (2019). A Visual Exploration of Gaussian Processes. Distill
• Videos and tutorials from the Gaussian Process Summer School: GPSS 2021 Program
  • Start with the first video, “Intro to GPs”, and the sessions on “Kernel Design” and “Representation Learning with GPs” (other videos can be explored later as time permits).
• Tutorials/workshops (Jupyter notebooks): GPSS 2021 Labs
• The GP Bible by Rasmussen and Williams (2006): Gaussian Processes for Machine Learning

Bayesian Optimization

• Exploring Bayesian Optimization (Agnihotri and Batra 2020). Distill
• Frazier (2018). A Tutorial on Bayesian Optimization. arXiv
• Video: “Introduction to Bayesian Optimization” from the Gaussian Process Summer School, Day 3: GPSS 2021 Day 3
• The Bayesian Optimization Book by Garnett (2023): BayesOptBook

Slack Channel

• Join and check out the #gaussian-processes channel on the lab Slack.

Agnihotri, Apoorv, and Nipun Batra. 2020. “Exploring Bayesian Optimization.” Distill. https://doi.org/10.23915/distill.00026.

Garnett, Roman. 2023. Bayesian Optimization. Cambridge University Press.

Rasmussen, Carl Edward, and Christopher KI Williams. 2006. Gaussian Processes for Machine Learning. Vol. 2. 3. MIT press Cambridge, MA.