Bayesian Optimization

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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

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

  1. 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

    Department of Chemical and Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, 53706, Wisconsin, USA. · Department of Chemical and Biomolecular Engineering, The Ohio State University, 151 W. Woodruf Avenue, Columbus, 43210, Ohio, USA. · Department of Computing, Imperial College London, Exhibition Rd, South Kensington, SW7 2AZ, London, United Kingdom.

  2. Collaborative Contextual Bayesian Optimization

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

    Department of Mathematics, Imperial College London, London, United Kingdom · Department of Industrial & Operations Engineering, University of Michigan, Ann Arbor, MI, USA · Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI, USA +1

  3. QuickScope: Certifying Hard Questions in Dynamic LLM Benchmarks

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

    Department of Computer Science University of British Columbia Vancouver, BC

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

    Apr 19, 2026Christian LysenstøenLLM Inference EfficiencyLLM Serving

    Inland Norway University of Applied Sciences · Visiting Student, University of California, Berkeley

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

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

    Department of Computer Science, Aalto University, Espoo, Finland · ELLIS Institute Finland · Department of Computer Science, University of Manchester, Manchester, United Kingdom

  6. 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

    MRC Biostatistics Unit, University of Cambridge, UK · Centre for AI, Data Science and Artificial Intelligence, R&D, AstraZeneca, Barcelona, Spain

  7. Optimization with SpotOptim

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

    Bartz & Bartz GmbH, 51643 Gummersbach, Germany

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

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

    Laboratory for Laser Energetics, Rochester, NY, USA · Department of Mechanical Engineering, University of Rochester, Rochester, NY, USA · Hewlett Packard Labs, Santa Clara, CA, USA +2

  9. 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

    School of Computer Science, University of Birmingham · School of Mathematics, University of Birmingham

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

    Apr 10, 2026Donney Fan, Geoff PleissBayesian OptimizationThompson Sampling

    University of British Columbia Vector Institute

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

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

    Department of Applied Physics, Aalto University, Puumiehenkuja 2, Espoo, 02320, Finland · School of Natural Sciences Physics Department, Technical University of Munich, James-Franck-Str. 1, Garching bei München, 85748, Germany · Atomistic Modeling Center, Munich Data Science Institute, Technical University of Munich, Walther-von-Dyck Str. 10, Garching bei München, 85748, Germany +1

  12. 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

    College of Electrical and Information Engineering at Hunan University · China Mobile Group Hunan Company Limited, Changsha 410082, China

  13. Preferential Bayesian Optimization with Crash Feedback

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

    Institute for Data Science in Mechanical Engineering (DSME), RWTH Aachen University, Aachen, Germany · aiXopt GmbH, Aachen, Germany

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

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

    The Hong Kong University of Science and Technology (Guangzhou) · Huawei Noah’s Ark Lab · University of Science and Technology of China +5

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

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

    Cyber-physical Systems Group, Aalto University, Espoo, Finland · School of Engineering Sciences, Lappeenranta–Lahti University of Technology LUT, Lappeenranta, Finland · Department of Information Technology, Uppsala University, Uppsala, Sweden

  16. mlr3mbo: Bayesian Optimization in R

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

    Department of Statistics, LMU Munich, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany · University of St Andrews, St Andrews, Scotland

  17. Transfer Learning in Bayesian Optimization for Aircraft Design

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

    1*Department of Mechanical Engineering, McGill University, Canada. · 2Advanced Product Development, Bombardier, Canada. · Department of Mathematical and Industrial Engineering, Polytechnique Montréal, Canada. +4

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

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

    University of Illinois Chicago, IL, USA

  19. 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

    Department of Computer Science, University of Manchester, UK · Centre for AI in Assistive Autonomy, University of Edinburgh, Scotland, UK · Department of Computer Science, Aalto University, Espoo, Finland +2

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

    Mar 27, 2026Antonio Candelieri, Laurens BliekBayesian Optimization

    Department of Economics Management and Statistics, University of Milano-Bicocca, Milan, Italy. · Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, the Netherlands. · Eindhoven AI Systems Institute, Eindhoven, the Netherlands.

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

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

    Faculty of Electrical Engineering, TU Eindhoven, The Netherlands

  22. Practical Efficient Global Optimization is No-regret

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

    Lawrence Livermore National Laboratory, CA, USA · National University of Singapore, Singapore · National Laboratory of the Rockies, CO, USA

  23. Memory-Guided Trust-Region Bayesian Optimization (MG-TuRBO) for High Dimensions

    Mar 25, 2026Abhilasha Saroj, Shaked Regev, Guanhao Xu +3Bayesian OptimizationBlack-Box Optimization

  24. Trust Region Constrained Bayesian Optimization with Penalized Constraint Handling

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

    Statistical Quality Control and Operations Research Unit, Indian Statistical Institute, Kolkata, India.

  25. 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

    Control and Cyber-Physical Systems Laboratory, Technical University of Darmstadt, Darmstadt, Germany · Volkswagen AG, Wolfsburg, Germany

  26. ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization

    Mar 22, 2026Foo Hui-Mean, Yuan-chin I ChangSequential Experimental DesignActive Experimental Design

    Institute of Statistical Science, Academia Sinica, Taipei, Taiwan

  27. ReBOL: Retrieval via Bayesian Optimization with Batched LLM Relevance Observations and Query Reformulation

    Mar 20, 2026Anton Korikov, Scott SannerInformation RetrievalLLM Reranking

    University of Toronto

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

    Mar 19, 2026Arundhathi Dev, Justin ZhanSparse AttentionHyperparameter Optimization

    Department of Computer Science, University of Cincinnati, Cincinnati, USA

  29. Standard Acquisition Is Sufficient for Asynchronous Bayesian Optimization

    Mar 13, 2026Ben Riegler, James Odgers, Vincent FortuinBayesian OptimizationThompson Sampling

    Technical University of Munich Helmholtz AI MCML · UTN Helmholtz AI MCML

  30. Human-AI Collaborative Autonomous Experimentation With Proxy Modeling for Comparative Observation

    Mar 13, 2026Arpan Biswas, Hiroshi Funakubo, Yongtao LiuAutonomous ExperimentationBayesian Optimization

    University of Tennessee-Oak Ridge Innovation Institute, University of Tennessee, Knoxville, TN 37996, USA · Department of Material Science and Engineering, Institute of Science Tokyo, Yokohama, 226-8502, Japan · Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA