This repository contains the code and experimental results for the paper "Enhancing Batch Diversity in Surrogate Optimization: A Determinantal Point Processes Approach." It provides implementations…

Code related to the paper "Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation"

Python implementation of the MACE Bayesian optimization algorithm, with GPy used as the backend GP library

Parallel Bayesian Optimization in R for Quantile Regression Forests and non-crossing quantiles

ϵ-shotgun: ϵ-greedy Batch Bayesian Optimisation

Batched Energy-Entropy acquisition for Bayesian Optimization (NeurIPS 2024)

Official implementation of the 'Batch Bayesian Optimization with adaptive batch acquisition functions via multi-objective optimization' by Jixiang Chen, Fu Luo, Genghui Li, and Zhenkun Wang.

Bayesian optimization with Standard Gaussian Processes on high dimensional benchmarks

Book: Introduction to Python for Computational Science and Engineering

Numerical Black-Box Optimization Benchmarking Framework

This is source code for Surrogate-Assisted Evolutionary Algorithm with Model and Infill Criterion Auto-Configuration.

for testing metaheuristic algorithm which is specific for continuous search spaces like Particle Swarm optimizations, Differential evolutions, etc, one can be sure about the performances of algorit…

code for the ICML2018 paper "Batch Bayesian Optimization via Multi-objective Acquisition Ensemble for Automated Analog Circuit Design"

Parallelised Thompson Sampling in GPs for Bayesian Optimisation

Collection of open source hypervolume codes that have been standardized to work with the MOEA Framework.

[TMLR' 24] High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy

Official implementation of NeurIPS'22 paper "Monte Carlo Tree Search based Variable Selection for High-Dimensional Bayesian Optimization"

国家自然科学基金申请书正文（面上项目）LaTeX 模板（非官方）

SAASBO: a package for high-dimensional bayesian optimization

Scalable Bayesian Optimization with Generalized Product of Experts

Engineering applications of multi-objective evolutionary algorithms: A test suite of box-constrained real-world problems

A set of real-world multi-objective optimization problems

手写实现李航《统计学习方法》书中全部算法

Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.

本模板是基于LaTeX的beamer模板类制作的西南交通大学非官方幻灯片模板

A fast exact algorithm calculating Expected HyperVolume Improvement (EHVI)