mlsanityData to 7 Oct 2026

BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits

arXiv 1405.7430 ↗First posted 29 May 2014cs.LGcited by 18

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Abstract (arXiv)

BayesOpt is a library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems. Bayesian optimization is sample efficient by building a posterior distribution to capture the evidence and prior knowledge for the target function. Built in standard C++, the library is extremely efficient while being portable and flexible. It includes a common interface for C, C++, Python, Matlab and Octave.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 May 2014.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 3; 2023: 3; 2024: 5; 2025: 2; 2026: 3.

18 papers.

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  1. 2023Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlowcited by 11
  2. 2021Revisiting Bayesian Optimization in the light of the COCO benchmarkcited by 10
  3. 2022Scalable First-Order Bayesian Optimization via Structured Automatic Differentiationcited by 10
  4. 2024X Hacking: The Threat of Misguided AutoMLcited by 5
  5. 2023Designing Optimal Behavioral Experiments Using Machine Learningcited by 3
  6. 2024Enhanced Bayesian Optimization via Preferential Modeling of Abstract Propertiescited by 3
  7. 2021A Genetic Algorithm with Tree-structured Mutation for Hyperparameter Optimisation of Graph Neural Networkscited by 2
  8. 2022Looking at the posterior: accuracy and uncertainty of neural-network predictionscited by 2
  9. 2024Stein Boltzmann Sampling: A Variational Approach for Global Optimizationcited by 2
  10. 2024Bayesian optimization for robust robotic grasping using a sensorized compliant handcited by 2
  11. 2025Leveraging semantic similarity for experimentation with AI-generated treatmentscited by 1
  12. 2022MEESO: A Multi-objective End-to-End Self-Optimized Approach for Automatically Building Deep Learning Modelscited by 0
6 more
  1. 2023IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonicscited by 0
  2. 2024Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systemscited by 0
  3. 2025Multi-view diffusion geometry using intertwined diffusion trajectoriescited by 0
  4. 2026Practical Efficient Global Optimization is No-regretcited by 0
  5. 2026mlr3mbo: Bayesian Optimization in Rcited by 0
  6. 2026Beyond Gradient Descent: Adam for Analog Ising Machinescited by 0