Maximizing acquisition functions for Bayesian optimization

25 May 2018

Papers citing "Maximizing acquisition functions for Bayesian optimization"

50 / 117 papers shown

Title
Why risk matters for protein binder design Tudor-Stefan Cotet Igor Krawczuk 43 0 0 31 Mar 2025
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization Toby Boyne Jose Pablo Folch Robert M. Lee B. Shafei Ruth Misener GP 59 0 0 07 Mar 2025
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do? Anastasia S. Georgiou Daniel Jungen Luise F. Kaven Verena Hunstig Constantine Frangakis Ioannis G. Kevrekidis Alexander Mitsos 41 0 0 05 Mar 2025
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization Natalie Maus Kyurae Kim Yimeng Zeng Haydn Thomas Jones Fangping Wan Marcelo Der Torossian Torres Cesar de la Fuente-Nunez Jacob R. Gardner 80 0 0 31 Jan 2025
Unexpected Improvements to Expected Improvement for Bayesian Optimization Sebastian Ament Sam Daulton David Eriksson Maximilian Balandat E. Bakshy 51 69 0 08 Jan 2025
Rate-Informed Discovery via Bayesian Adaptive Multifidelity Sampling Aman Sinha Payam Nikdel Supratik Paul Shimon Whiteson 76 0 0 26 Nov 2024
Optimizing Posterior Samples for Bayesian Optimization via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang 114 2 0 29 Oct 2024
Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation Yilin Xie Shiqiang Zhang J. Paulson Calvin Tsay 28 5 0 22 Oct 2024
Batched Energy-Entropy acquisition for Bayesian Optimization Felix Teufel Carsten Stahlhut J. Ferkinghoff-Borg 33 0 0 11 Oct 2024
Gaussian Process Thompson Sampling via Rootfinding Taiwo A. Adebiyi Bach Do Ruda Zhang GP 25 3 0 10 Oct 2024
Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems Markus Grimm Sébastien Paul Pierre Chainais 32 0 0 05 Aug 2024
Uncertainty-Guided Optimization on Large Language Model Search Trees Julia Grosse Ruotian Wu Ahmad Rashid Philipp Hennig Pascal Poupart Agustinus Kristiadi 37 1 0 04 Jul 2024
Approximation-Aware Bayesian Optimization Natalie Maus Kyurae Kim Geoff Pleiss David Eriksson John P. Cunningham Jacob R. Gardner 29 2 0 06 Jun 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 29 3 0 18 Apr 2024
Model Uncertainty in Evolutionary Optimization and Bayesian Optimization: A Comparative Analysis Hao Hao Xiaoqun Zhang Aimin Zhou 24 3 0 21 Mar 2024
Reinforced In-Context Black-Box Optimization Lei Song Chenxiao Gao Ke Xue Chenyang Wu Dong Li Jianye Hao Zongzhang Zhang Chao Qian 32 3 0 27 Feb 2024
Stopping Bayesian Optimization with Probabilistic Regret Bounds James T. Wilson 31 4 0 26 Feb 2024
FlexHB: a More Efficient and Flexible Framework for Hyperparameter Optimization Yang Zhang Haiyang Wu Yuekui Yang 43 0 0 21 Feb 2024
An Augmented Surprise-guided Sequential Learning Framework for Predicting the Melt Pool Geometry Ahmed Shoyeb Raihan H. Khosravi T. Bhuiyan Imtiaz Ahmed AI4CE 17 7 0 10 Jan 2024
Integrated Path Tracking with DYC and MPC using LSTM Based Tire Force Estimator for Four-wheel Independent Steering and Driving Vehicle Sungjin Lim Bilal Sadiq Yongsik Jin Sangho Lee Gyeungho Choi Kanghyun Nam Yongseob Lim 19 0 0 13 Dec 2023
A General Framework for User-Guided Bayesian Optimization Carl Hvarfner Frank Hutter Luigi Nardi GP 44 11 0 24 Nov 2023
Bayesian Optimization of Function Networks with Partial Evaluations Poompol Buathong Jiayue Wan Raul Astudillo Sam Daulton Maximilian Balandat P. Frazier 26 2 0 03 Nov 2023
Adaptive importance sampling for heavy-tailed distributions via $α$ -divergence minimization Thomas Guilmeau Nicola Branchini Émilie Chouzenoux Victor Elvira 34 2 0 25 Oct 2023
An Introduction to the Calibration of Computer Models Richard D. Wilkinson Christopher W. Lanyon 32 0 0 13 Oct 2023
Smartpick: Workload Prediction for Serverless-enabled Scalable Data Analytics Systems Anshuman Mohapatra Kwangsung Oh 24 2 0 25 Jul 2023
Physics-based Reduced Order Modeling for Uncertainty Quantification of Guided Wave Propagation using Bayesian Optimization G. Drakoulas T. Gortsas D. Polyzos 32 2 0 18 Jul 2023
MALIBO: Meta-learning for Likelihood-free Bayesian Optimization Jia-Yu Pan Stefan Falkner Felix Berkenkamp Joaquin Vanschoren 34 1 0 07 Jul 2023
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How Sebastian Pineda Arango Fabio Ferreira Arlind Kadra Frank Hutter Frank Hutter Josif Grabocka 29 15 0 06 Jun 2023
Is novelty predictable? Clara Fannjiang Jennifer Listgarten AI4CE 17 14 0 01 Jun 2023
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks Ji Won Park Natavsa Tagasovska Michael R. Maser Stephen Ra Kyunghyun Cho 24 6 0 01 Jun 2023
DATED: Guidelines for Creating Synthetic Datasets for Engineering Design Applications Cyril Picard Jürg Schiffmann Faez Ahmed 32 8 0 15 May 2023
NUBO: A Transparent Python Package for Bayesian Optimization Mike Diessner Kevin J. Wilson Richard D. Whalley 46 2 0 11 May 2023
Adaptive Experimentation at Scale: A Computational Framework for Flexible Batches Ethan Che Hongseok Namkoong OffRL 31 1 0 21 Mar 2023
BO-Muse: A human expert and AI teaming framework for accelerated experimental design Sunil R. Gupta A. Shilton V. ArunKumarA. S. Ryan Majid Abdolshah Hung Le Santu Rana Julian Berk Mahad Rashid Svetha Venkatesh 34 7 0 03 Mar 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization Jiayu Zhao Renyu Yang Shenghao Qiu Zheng Wang 11 4 0 16 Feb 2023
Scalable Bayesian optimization with high-dimensional outputs using randomized prior networks Mohamed Aziz Bhouri M. Joly Robert Yu S. Sarkar P. Perdikaris BDL UQCV AI4CE 19 1 0 14 Feb 2023
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces I. Azangulov A. Smolensky Alexander Terenin Viacheslav Borovitskiy 32 14 0 30 Jan 2023
Cell-Free Data Power Control Via Scalable Multi-Objective Bayesian Optimisation Sergey S. Tambovskiy Gábor Fodor H. Tullberg 12 3 0 20 Dec 2022
A Data-Driven Evolutionary Transfer Optimization for Expensive Problems in Dynamic Environments Ke Li Renzhi Chen Xin Yao 24 14 0 05 Nov 2022
Fantasizing with Dual GPs in Bayesian Optimization and Active Learning Paul E. Chang Prakhar Verma S. T. John Victor Picheny Henry B. Moss Arno Solin GP 25 6 0 02 Nov 2022
Atlas: Automate Online Service Configuration in Network Slicing Qiang Liu Nakjung Choi Tao Han 15 7 0 30 Oct 2022
Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization Sam Daulton Xingchen Wan David Eriksson Maximilian Balandat Michael A. Osborne E. Bakshy 27 36 0 18 Oct 2022
Pareto Set Learning for Expensive Multi-Objective Optimization Xi Lin Zhiyuan Yang Xiao-Yan Zhang Qingfu Zhang 36 54 0 16 Oct 2022
Hyperactive Learning (HAL) for Data-Driven Interatomic Potentials Cas van der Oord Matthias Sachs D. P. Kovács Christoph Ortner Gábor Csányi 41 64 0 09 Oct 2022
Joint Entropy Search for Multi-objective Bayesian Optimization Ben Tu Axel Gandy N. Kantas B. Shafei 21 38 0 06 Oct 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies W. Neiswanger Lantao Yu Shengjia Zhao Chenlin Meng Stefano Ermon UQCV 45 11 0 04 Oct 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees Rafael Oliveira Louis C. Tiao Fabio Ramos 42 7 0 22 Sep 2022
Batch Bayesian Optimization via Particle Gradient Flows Enrico Crovini S. Cotter K. Zygalakis Andrew B. Duncan 13 3 0 10 Sep 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 24 3 0 04 Aug 2022
Investigating Bayesian optimization for expensive-to-evaluate black box functions: Application in fluid dynamics Mike Diessner Joseph O’Connor A. Wynn S. Laizet Yu Guan Kevin J. Wilson Richard D. Whalley 33 18 0 19 Jul 2022