mlsanityData to 7 Oct 2026

BOSS: Bayesian Optimization over String Spaces

arXiv 2010.00979 ↗First posted 2 Oct 2020cs.LG cs.AI stat.MLcited by 54

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Abstract (arXiv)

This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops. Recent applications of BO over strings have been hindered by the need to map inputs into a smooth and unconstrained latent space. Learning this projection is computationally and data-intensive. Our approach instead builds a powerful Gaussian process surrogate model based on string kernels, naturally supporting variable length inputs, and performs efficient acquisition function maximization for spaces with syntactical constraints. Experiments demonstrate considerably improved optimization over existing approaches across a broad range of constraints, including the popular setting where syntax is governed by a context-free grammar.

Key facts. Cited by 54 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Oct 2020.

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Citing papers per year: 2021: 7; 2022: 10; 2023: 16; 2024: 6; 2025: 10; 2026: 5.

54 papers.

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  2. 2021High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learningcited by 54
  3. 2023A Study of Bayesian Neural Network Surrogates for Bayesian Optimizationcited by 50
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  5. 2021GIBBON: General-purpose Information-Based Bayesian OptimisatioNcited by 47
  6. 2022Reinforced Genetic Algorithm for Structure-based Drug Designcited by 46
  7. 2021Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spacescited by 45
  8. 2022GAUCHE: A Library for Gaussian Processes in Chemistrycited by 40
  9. 2022Group SELFIES: A Robust Fragment-Based Molecular String Representationcited by 32
  10. 2023Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisationcited by 32
  11. 2023Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequencescited by 23
  12. 2024A survey and benchmark of high-dimensional Bayesian optimization of discrete sequencescited by 22
38 more
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  4. 2023Searching for High-Value Molecules Using Reinforcement Learning and Transformerscited by 18
  5. 2021Risk-averse Heteroscedastic Bayesian Optimizationcited by 17
  6. 2021Bayesian Optimization over Permutation Spacescited by 17
  7. 2023Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimizationcited by 15
  8. 2022AntBO: Towards Real-World Automated Antibody Design with Combinatorial Bayesian Optimisationcited by 14
  9. 2021Adaptive machine learning for protein engineeringcited by 13
  10. 2022Molecule Generation for Drug Design: a Graph Learning Perspectivecited by 13
  11. 2023DiscoBAX: Discovery of Optimal Intervention Sets in Genomic Experiment Designcited by 12
  12. 2023Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlowcited by 11
  13. 2024Kermut: Composite kernel regression for protein variant effectscited by 11
  14. 2023Deep Learning Methods for Small Molecule Drug Discovery: A Surveycited by 10
  15. 2022Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammarscited by 9
  16. 2022ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolutioncited by 5
  17. 2024Be aware of overfitting by hyperparameter optimization!cited by 5
  18. 2022Fourier Representations for Black-Box Optimization over Categorical Variablescited by 4
  19. 2022Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributionscited by 4
  20. 2024Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Designcited by 4
  21. 2022Sample-Efficient Optimisation with Probabilistic Transformer Surrogatescited by 3
  22. 2023Joint Design of Protein Sequence and Structure based on Motifscited by 3
  23. 2023Molecular De Novo Design through Transformer-based Reinforcement Learningcited by 3
  24. 2023Functional Geometry Guided Protein Sequence and Backbone Structure Co-Designcited by 2
  25. 2025GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidancecited by 2
  26. 2025Multi-fidelity batch Bayesian optimization for bioprocess development across scalescited by 2
  27. 2025Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimizationcited by 2
  28. 2023Inverse Protein Folding Using Deep Bayesian Optimizationcited by 1
  29. 2025InversionGNN: A Dual Path Network for Multi-Property Molecular Optimizationcited by 1
  30. 2025A Guide to Bayesian Optimization in Bioprocess Engineeringcited by 1
  31. 2025Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimizationcited by 1
  32. 2026Regret Analysis of Guided Diffusion for Black-Box Optimization over Structured Inputscited by 1
  33. 2026Embedding by Elicitation: Dynamic Representations for Bayesian Optimization of System Promptscited by 1
  34. 2026Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimizationcited by 1
  35. 2023Applications of Gaussian Processes at Extreme Lengthscales: From Molecules to Black Holescited by 0
  36. 2024Simulation Based Bayesian Optimizationcited by 0
  37. 2025Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operationscited by 0
  38. 2025MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioningcited by 0

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