Survey
 Recent Advances in Bayesian Optimization
 Proceeding of IEEE Taking the Human Out of the Loop: A Review of Bayesian Optimization # 3486
 A Survey on Highdimensional Gaussian Process Modeling with Application to Bayesian Optimization
 Expected improvement for expensive optimization: a review
Tutorial
 Exploring Bayesian Optimization
 Bayesian optimization  Martin Krasser's Blog
 How to Implement Bayesian Optimization from Scratch in Python
 Tutorial #8: Bayesian optimization  Borealis AI
 Lecture 12 Bayesian Optimization from CSE 515T: Bayesian Methods in Machine Learning – Fall 2019
 GitHub  krasserm/bayesianmachinelearning: Notebooks about Bayesian methods for machine learning
 [1807.02811] A Tutorial on Bayesian Optimization
 coding book Bayesian Optimization: Theory and Practice Using Python  SpringerLink
CO & HiDim
 NuerIPS 19 # 65 COMBO, Combinatorial Bayesian Optimization using the Graph Cartesian Product
– risky, graph kernal at 2.2, 2.3 worthy reading  ICML # 110 BOCS, Bayesian Optimization of Combinatorial Structures
– math flavor  NuerIPS 19, # 240, TuRBO,Scalable Global Optimization via Local Bayesian Optimization # 230
– improved BOS, engineering flavor  ICML 22, # 25, Casmopolitan, Think Global and Act Local: Bayesian Optimisation over HighDimensional Categorical and Mixed Search Spaces
– [Code]  NuerIPS 22, # 14, Local Latent Space Bayesian Optimization over Structured Inputs
 UAI 21, SAAS, # 39, HighDimensional Bayesian Optimization with Sparse AxisAligned Subspaces
 NuerIPS 22, # 6, Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization
 AISTATS 23, #0, BODi, [2303.01774] Bayesian Optimization over HighDimensional Combinatorial Spaces via Dictionarybased Embeddings
– worthy reading
Optional
 GitHub  automl/SMAC3: SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
 OG BO GitHub  fmfn/BayesianOptimization: A Python implementation of global optimization with gaussian processes.
Convergence Rate
 [1101.3501] Convergence rates of efficient global optimization algorithms
 Convergence properties of the expected improvement algorithm with fixed mean and covariance functions  ScienceDirect
 https://pubsonline.informs.org/doi/abs/10.1287/opre.2016.1494
 Examples of inconsistency in optimization by expected improvement  SpringerLink
Paper
 NeurIPS 2012 Practical Bayesian Optimization of Machine Learning Algorithms # 7179
 https://hess.copernicus.org/preprints/hess2017377/hess2017377.pdf
Source Code
 GitHub  pytorch/botorch: Bayesian optimization in PyTorch, # 2.6k stars
 GitHub  fmfn/BayesianOptimization: A Python implementation of global optimization with gaussian processes. # 6.7k stars
 GitHub  pyroppl/pyro: Deep universal probabilistic programming with Python and PyTorch, # 8k stars
Gaussian Process
 [the Book!] Gaussian process for machine learning
 A Visual Exploration of Gaussian Processes

[2009.10862] An Intuitive Tutorial to Gaussian Processes Regression
– GitHub  jwangjie/GaussianProcessesRegressionTutorial: An Intuitive Tutorial to Gaussian Processes Regression  Implement A Gaussian Process From Scratch  by Shuai Guo  Towards Data Science
 Gaussian Processes, not quite for dummies
 GaussianProcessRegressionhandout/GPR_handout.pdf at master · NicolasDurrande/GaussianProcessRegressionhandout · GitHub