Overview

Bayesian optimization studies how to find good inputs to an expensive or unknown process—such as a simulation, experiment, or model configuration—using as few evaluations as possible. It typically fits a probabilistic surrogate, often a Gaussian process, then uses an acquisition function to balance trying promising inputs with exploring uncertain ones. Current approaches extend this loop with trust regions, multi-fidelity data, constraints, multiple objectives, changing conditions, and human or language-model guidance. A central challenge is choosing models and search strategies that remain reliable in high-dimensional or structured spaces without making inference and candidate selection too costly; theoretical guarantees do not always predict practical performance.

Latest papers

CardsList

243 papers45 papers in the last four weeks, up 36% on the four weeks before. 0.3% of all new papers.

  1. FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision

    Apr 23, 2026Nathan Shankar, Pawel Ladosz, Hujun YinImage EnhancementBayesian Optimization

  2. HARBOR: Automated Harness Optimization

    Apr 22, 2026Biswa Sengupta, Jinhua WangBayesian OptimizationAgent Harness Optimization

  3. An Efficient Spatial Branch-and-Bound Algorithm for Global Optimization of Gaussian Process Posterior Mean Functions

    Apr 21, 2026Wei-Ting Tang, Akshay Kudva, Calvin Tsay +1Bayesian OptimizationGlobal Optimization

  4. Collaborative Contextual Bayesian Optimization

    Apr 20, 2026Chih-Yu Chang, Qiyuan Chen, Tianhan Gao +5Bayesian Optimization

  5. QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks

    Apr 20, 2026Taylor Lundy, Narun K. Raman, Kevin Leyton-BrownLLM EvaluationBayesian Optimization

  6. SLO-Guard: Crash-Aware, Budget-Consistent Autotuning for SLO-Constrained LLM Serving

    Apr 19, 2026Christian LysenstøenLLM Inference EfficiencyLLM Serving

  7. Multi-Objective Bayesian Optimization via Adaptive \varepsilon-Constraints Decomposition

    Apr 17, 2026Yaohong Yang, Sammie Katt, Samuel KaskiBayesian OptimizationMulti-Objective Optimization

  8. BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization

    Apr 15, 2026Jackie Rao, Ferran Gonzalez Hernandez, Leon Gerard +1Protein DesignSurrogate-Assisted Optimization

  9. Optimization with SpotOptim

    Apr 15, 2026Thomas Bartz-BeielsteinBlack-Box OptimizationSurrogate-Assisted Optimization

  10. BayMOTH: Bayesian optiMizatiOn with meTa-lookahead -- a simple approacH

    Apr 13, 2026Rahman Ejaz, Varchas Gopalaswamy, Ricardo Luna +5Bayesian OptimizationMulti-Task Optimization

  11. Do We Really Need to Approach the Entire Pareto Front in Many-Objective Bayesian Optimisation?

    Apr 10, 2026Chao Jiang, Jingyu Huang, Miqing LiMulti-Objective OptimizationBayesian Optimization

  12. Adaptive Candidate Point Thompson Sampling for High-Dimensional Bayesian Optimization

    Apr 10, 2026Donney Fan, Geoff PleissBayesian OptimizationThompson Sampling

  13. Bayesian Optimization for Mixed-Variable Problems in the Natural Sciences

    Apr 8, 2026Yuhao Zhang, Ti John, Matthias Stosiek +1Bayesian Optimization

  14. Multi-Agent Pathfinding with Non-Unit Integer Edge Costs via Enhanced Conflict-Based Search and Graph Discretization

    Apr 7, 2026Hongkai Fan, Qinjing Xie, Bo Ouyang +4Safe Interval Path PlanningMulti-Agent Path Finding

  15. Preferential Bayesian Optimization with Crash Feedback

    Apr 2, 2026Johanna Menn, David Stenger, Sebastian TrimpeBayesian OptimizationSafe Bayesian Optimization

  16. Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial

    Apr 1, 2026Zhongwei Yu, Rasul Tutunov, Alexandre Max Maraval +13Bayesian OptimizationScientific Discovery

  17. Safe learning-based control via function-based uncertainty quantification

    Apr 1, 2026Abdullah Tokmak, Toni Karvonen, Thomas B. Schön +1Uncertainty QuantificationSafety-Critical Control

  18. mlr3mbo: Bayesian Optimization in R

    Mar 31, 2026Marc Becker, Lennart Schneider, Martin Binder +2Bayesian OptimizationHyperparameter Optimization

  19. Transfer Learning in Bayesian Optimization for Aircraft Design

    Mar 30, 2026Ali Tfaily, Youssef Diouane, Nathalie Bartoli +1Bayesian OptimizationSurrogate-Assisted Optimization

  20. Multi-Agent LLMs for Adaptive Acquisition in Bayesian Optimization

    Mar 30, 2026Andrea Carbonati, Mohammadsina Almasi, Hadis AnahidehLarge Language Model-Guided OptimizationExploration-Exploitation Tradeoff

  21. Active Preference Learning over Latent Preference Archetypes for Many-Objective Bayesian Optimization

    Mar 30, 2026Manisha Dubey, Sebastiaan De Peuter, Wanrong Wang +1Active Preference LearningBayesian Optimization

  22. Optimal Transport-based Permutation-Invariant Bayesian Optimization of Offshore Wind Farm Layouts

    Mar 27, 2026Antonio Candelieri, Laurens BliekBayesian Optimization

  23. Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization

    Mar 27, 2026Ajith Anil Meera, Wouter KouwFree Energy CalculationBayesian Optimization

  24. Practical Efficient Global Optimization is No-regret

    Mar 26, 2026Jingyi Wang, Haowei Wang, Nai-Yuan Chiang +3Bayesian OptimizationGlobal Optimization

  25. Trust Region Constrained Bayesian Optimization with Penalized Constraint Handling

    Mar 25, 2026Raju Chowdhury, Tanmay Sen, Biswabrata PradhanBayesian OptimizationBlack-Box Optimization

  26. Efficient Controller Learning from Human Preferences and Numerical Data Via Multi-Modal Surrogate Models

    Mar 25, 2026Lukas Theiner, Maik Pfefferkorn, Yongpeng Zhao +2Bayesian OptimizationMulti-Fidelity Optimization

  27. Self-Tuning Sparse Attention: Multi-Fidelity Hyperparameter Optimization for Transformer Acceleration

    Mar 19, 2026Arundhathi Dev, Justin ZhanSparse AttentionHyperparameter Optimization