Saved in:
| Main Authors: | Buathong, Poompol, Frazier, Peter I. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.11456 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bayesian Optimization of Function Networks with Partial Evaluations
by: Buathong, Poompol, et al.
Published: (2023)
by: Buathong, Poompol, et al.
Published: (2023)
Better Protein Function Prediction by Modeling Survivorship Bias
by: Chao, Zhongmou, et al.
Published: (2026)
by: Chao, Zhongmou, et al.
Published: (2026)
Cost-aware Stopping for Bayesian Optimization
by: Xie, Qian, et al.
Published: (2025)
by: Xie, Qian, et al.
Published: (2025)
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
by: Xie, Qian, et al.
Published: (2024)
by: Xie, Qian, et al.
Published: (2024)
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
by: Tan, Samuel, et al.
Published: (2024)
by: Tan, Samuel, et al.
Published: (2024)
Concentration and Calibration in Predictive Bayesian Inference
by: Frazier, David T., et al.
Published: (2026)
by: Frazier, David T., et al.
Published: (2026)
Fast Estimation of Partial Dependence Functions using Trees
by: Liu, Jinyang, et al.
Published: (2024)
by: Liu, Jinyang, et al.
Published: (2024)
Structured Partial Stochasticity in Bayesian Neural Networks
by: Rochussen, Tommy
Published: (2024)
by: Rochussen, Tommy
Published: (2024)
Multi-Armed Bandits with Interference
by: Jia, Su, et al.
Published: (2024)
by: Jia, Su, et al.
Published: (2024)
Fast, Precise Thompson Sampling for Bayesian Optimization
by: Sweet, David
Published: (2024)
by: Sweet, David
Published: (2024)
Bayesian Optimization of Partially Known Systems using Hybrid Models
by: Cramer, Eike, et al.
Published: (2026)
by: Cramer, Eike, et al.
Published: (2026)
Partially Stochastic Infinitely Deep Bayesian Neural Networks
by: Calvo-Ordonez, Sergio, et al.
Published: (2024)
by: Calvo-Ordonez, Sergio, et al.
Published: (2024)
Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization
by: Irie, Kaichi, et al.
Published: (2025)
by: Irie, Kaichi, et al.
Published: (2025)
Function-on-Function Bayesian Optimization
by: Huang, Jingru, et al.
Published: (2025)
by: Huang, Jingru, et al.
Published: (2025)
Partial Trace-Class Bayesian Neural Networks
by: Carter, Arran, et al.
Published: (2025)
by: Carter, Arran, et al.
Published: (2025)
Dynamic Bayesian Optimization Framework for Instruction Tuning in Partial Differential Equation Discovery
by: Qu, Junqi, et al.
Published: (2025)
by: Qu, Junqi, et al.
Published: (2025)
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
by: Li, Yucen Lily, et al.
Published: (2023)
by: Li, Yucen Lily, et al.
Published: (2023)
Smooth Non-Stationary Bandits
by: Jia, Su, et al.
Published: (2023)
by: Jia, Su, et al.
Published: (2023)
Bayesian Neural Networks for Functional ANOVA model
by: Park, Seokhun, et al.
Published: (2025)
by: Park, Seokhun, et al.
Published: (2025)
Generative Bayesian Optimization: Generative Models as Acquisition Functions
by: Oliveira, Rafael, et al.
Published: (2025)
by: Oliveira, Rafael, et al.
Published: (2025)
Bayesian Optimization of Functions over Node Subsets in Graphs
by: Liang, Huidong, et al.
Published: (2024)
by: Liang, Huidong, et al.
Published: (2024)
Experimenting, Fast and Slow: Bayesian Optimization of Long-term Outcomes with Online Experiments
by: Feng, Qing, et al.
Published: (2025)
by: Feng, Qing, et al.
Published: (2025)
Bridging GANs and Bayesian Neural Networks via Partial Stochasticity
by: Filippone, Maurizio, et al.
Published: (2025)
by: Filippone, Maurizio, et al.
Published: (2025)
Simulation-based Bayesian inference under model misspecification
by: Kelly, Ryan P., et al.
Published: (2025)
by: Kelly, Ryan P., et al.
Published: (2025)
Regime-Conditioned Evaluation in Multi-Context Bayesian Optimization
by: Thomas, Noel
Published: (2026)
by: Thomas, Noel
Published: (2026)
Partial Rankings of Optimizers
by: Rodemann, Julian, et al.
Published: (2024)
by: Rodemann, Julian, et al.
Published: (2024)
Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
by: Fotias, Sofianos Panagiotis, et al.
Published: (2025)
Towards Scalable Bayesian Optimization via Gradient-Informed Bayesian Neural Networks
by: Makrygiorgos, Georgios, et al.
Published: (2025)
by: Makrygiorgos, Georgios, et al.
Published: (2025)
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization
by: Zhao, Jiayu, et al.
Published: (2023)
by: Zhao, Jiayu, et al.
Published: (2023)
Functional Stochastic Gradient MCMC for Bayesian Neural Networks
by: Wu, Mengjing, et al.
Published: (2024)
by: Wu, Mengjing, et al.
Published: (2024)
Function-Space MCMC for Bayesian Wide Neural Networks
by: Pezzetti, Lucia, et al.
Published: (2024)
by: Pezzetti, Lucia, et al.
Published: (2024)
Bayesian Optimization on Networks
by: Li, Wenwen, et al.
Published: (2025)
by: Li, Wenwen, et al.
Published: (2025)
SGD with Partial Hessian for Deep Neural Networks Optimization
by: Sun, Ying, et al.
Published: (2024)
by: Sun, Ying, et al.
Published: (2024)
Fast Ergodic Search with Kernel Functions
by: Sun, Max Muchen, et al.
Published: (2024)
by: Sun, Max Muchen, et al.
Published: (2024)
Deterministic Global Optimization of the Acquisition Function in Bayesian Optimization: To Do or Not To Do?
by: Georgiou, Anastasia, et al.
Published: (2025)
by: Georgiou, Anastasia, et al.
Published: (2025)
Linear Noise Approximation Assisted Bayesian Inference on Mechanistic Model of Partially Observed Stochastic Reaction Network
by: Xu, Wandi, et al.
Published: (2024)
by: Xu, Wandi, et al.
Published: (2024)
Combinations of Fast Activation and Trigonometric Functions in Kolmogorov-Arnold Networks
by: Ta, Hoang-Thang, et al.
Published: (2025)
by: Ta, Hoang-Thang, et al.
Published: (2025)
Bayesian Risk-Sensitive Policy Optimization For MDPs With General Loss Functions
by: Wang, Xiaoshuang, et al.
Published: (2025)
by: Wang, Xiaoshuang, et al.
Published: (2025)
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
by: Aglietti, Virginia, et al.
Published: (2024)
by: Aglietti, Virginia, et al.
Published: (2024)
Utilising Gradient-Based Proposals Within Sequential Monte Carlo Samplers for Training of Partial Bayesian Neural Networks
by: Millard, Andrew, et al.
Published: (2025)
by: Millard, Andrew, et al.
Published: (2025)
Similar Items
-
Bayesian Optimization of Function Networks with Partial Evaluations
by: Buathong, Poompol, et al.
Published: (2023) -
Better Protein Function Prediction by Modeling Survivorship Bias
by: Chao, Zhongmou, et al.
Published: (2026) -
Cost-aware Stopping for Bayesian Optimization
by: Xie, Qian, et al.
Published: (2025) -
Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index
by: Xie, Qian, et al.
Published: (2024) -
Asymptotically Optimal Regret for Black-Box Predict-then-Optimize
by: Tan, Samuel, et al.
Published: (2024)