mlsanityData to 14 Oct 2026

Discovering Many Diverse Solutions with Bayesian Optimization

arXiv 2210.10953 ↗First posted 20 Oct 2022cs.LG cs.AIcited by 31

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Abstract (arXiv)

Bayesian optimization (BO) is a popular approach for sample-efficient optimization of black-box objective functions. While BO has been successfully applied to a wide range of scientific applications, traditional approaches to single-objective BO only seek to find a single best solution. This can be a significant limitation in situations where solutions may later turn out to be intractable. For example, a designed molecule may turn out to violate constraints that can only be reasonably evaluated after the optimization process has concluded. To address this issue, we propose Rank-Ordered Bayesian Optimization with Trust-regions (ROBOT) which aims to find a portfolio of high-performing solutions that are diverse according to a user-specified diversity metric. We evaluate ROBOT on several real-world applications and show that it can discover large sets of high-performing diverse solutions while requiring few additional function evaluations compared to finding a single best solution.

Key facts. Cited by 31 papers in the map (data through 14 Oct 2026). Builds on 35 of its 55 references that are in the map. First posted on arXiv 20 Oct 2022.

Builds on

35 of 55 references.

References · 35

  1. 2016Automatic chemical design using a data-driven continuous representation of moleculescited by 765
  2. 2018A Tutorial on Bayesian Optimizationcited by 744
  3. 2018Junction Tree Variational Autoencoder for Molecular Graph Generationcited by 652
  4. 2018GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Accelerationcited by 609
  5. 2015Illuminating search spaces by mapping elitescited by 425
  6. 2013Gaussian Processes for Big Datacited by 383
  7. 2016The CMA Evolution Strategy: A Tutorialcited by 377
  8. 2019Scalable Global Optimization via Local Bayesian Optimizationcited by 374
  9. 2018GuacaMol: Benchmarking Models for De Novo Molecular Designcited by 297
  10. 2013Bayesian Optimization in a Billion Dimensions via Random Embeddingscited by 182
  11. 2021Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020cited by 148
  12. 2015High Dimensional Bayesian Optimisation and Bandits via Additive Modelscited by 139
23 more
  1. 2020Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retrainingcited by 123
  2. 2017Batched Large-scale Bayesian Optimization in High-dimensional Spacescited by 117
  3. 2017Constrained Bayesian Optimization with Noisy Experimentscited by 104
  4. 2022Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoderscited by 102
  5. 2020Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimizationcited by 92
  6. 2015Predictive Entropy Search for Multi-objective Bayesian Optimizationcited by 88
  7. 2021Multi-Objective Bayesian Optimization over High-Dimensional Search Spacescited by 87
  8. 2020Scalable Constrained Bayesian Optimizationcited by 84
  9. 2020Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraintscited by 81
  10. 2022Local Latent Space Bayesian Optimization over Structured Inputscited by 79
  11. 2017Parallel and Distributed Thompson Sampling for Large-scale Accelerated Exploration of Chemical Spacecited by 76
  12. 2016Using Centroidal Voronoi Tessellations to Scale Up the Multi-dimensional Archive of Phenotypic Elites Algorithmcited by 66
  13. 2020Accelerating high-throughput virtual screening through molecular pool-based active learningcited by 59
  14. 2021High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learningcited by 54
  15. 2015A General Framework for Constrained Bayesian Optimization using Information-based Searchcited by 50
  16. 2018Data-Efficient Design Exploration through Surrogate-Assisted Illuminationcited by 38
  17. 2021Bayesian Algorithm Execution: Estimating Computable Properties of Black-box Functions Using Mutual Informationcited by 33
  18. 2021How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Moleculescited by 27
  19. 2020Good practices for Bayesian Optimization of high dimensional structured spacescited by 24
  20. 2020Quality Diversity for Multi-task Optimizationcited by 23
  21. 2019Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimizationcited by 16
  22. 2020BOP-Elites, a Bayesian Optimisation algorithm for Quality-Diversity searchcited by 15
  23. 2017The True Destination of EGO is Multi-local Optimizationcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 8; 2024: 10; 2025: 7; 2026: 5.

31 papers.

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  1. 2022Multi-Objective GFlowNetscited by 101
  2. 2023Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learningcited by 24
  3. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 23
  4. 2023The Behavior and Convergence of Local Bayesian Optimizationcited by 20
  5. 2025Latent Bayesian Optimization via Autoregressive Normalizing Flowscited by 19
  6. 2024Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Designcited by 17
  7. 2023Multi-Fidelity Active Learning with GFlowNetscited by 15
  8. 2025Return of the Latent Space COWBOYS: Re-thinking the use of VAEs for Bayesian Optimisation of Structured Spacescited by 14
  9. 2024Inversion-based Latent Bayesian Optimizationcited by 11
  10. 2023An Equivariant Generative Framework for Molecular Graph-Structure Co-Designcited by 10
  11. 2024Approximation-Aware Bayesian Optimizationcited by 8
  12. 2024Robust Gaussian Processes via Relevance Pursuitcited by 8
19 more
  1. 2023Pareto Optimization to Accelerate Multi-Objective Virtual Screeningcited by 6
  2. 2023Joint Composite Latent Space Bayesian Optimizationcited by 5
  3. 2023Expert-guided Bayesian Optimisation for Human-in-the-loop Experimental Design of Known Systemscited by 3
  4. 2024Expected Diverse Utility (EDU): Diverse Bayesian Optimization of Expensive Computer Simulatorscited by 3
  5. 2024BEACON: A Bayesian Optimization Inspired Strategy for Efficient Novelty Searchcited by 2
  6. 2024Batched Energy-Entropy acquisition for Bayesian Optimizationcited by 2
  7. 2024Stein Variational Evolution Strategiescited by 2
  8. 2023Inverse Protein Folding Using Deep Bayesian Optimizationcited by 1
  9. 2025Robust and Computation-Aware Gaussian Processescited by 1
  10. 2025Generative flow-based warm start of the variational quantum eigensolvercited by 1
  11. 2026Manifold Sampling via Entropy Maximizationcited by 1
  12. 2026Automated Kernel Discovery Towards Understanding High-dimensional Bayesian Optimizationcited by 1
  13. 2024Beyond Regrets: Geometric Metrics for Bayesian Optimizationcited by 0
  14. 2025Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimizationcited by 0
  15. 2025PepCompass: Navigating peptide embedding spaces using Riemannian Geometrycited by 0
  16. 2025Trust Region-Based Bayesian Optimisation to Discover Diverse Solutionscited by 0
  17. 2026Surrogate-Guided Quantum Discovery in Black-Box Landscapes with Latent-Quadratic Interaction Embedding Transformerscited by 0
  18. 2026Building informative materials datasets beyond targeted objectivescited by 0
  19. 2026Range-Aware Bayesian Optimization for Discovering Diverse Designs within Target Property Windowscited by 0