Imagen de Portada

BITS for GAPS: Bayesian Information-Theoretic Sampling for hierarchical GAussian Process Surrogates

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jones, Kyla D., Dowling, Alexander W.
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

ScaleBITS: Scalable Bitwidth Search for Hardware-Aligned Mixed-Precision LLMs
por: Li, Xinlin, et al.
Publicado: (2026)

Learning discrete Bayesian networks with hierarchical Dirichlet shrinkage
por: Dombowsky, Alexander, et al.
Publicado: (2025)

Information-Theoretic Proofs for Diffusion Sampling
por: Reeves, Galen, et al.
Publicado: (2025)

Bidirectional Information Flow (BIF) -- A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization
por: Guerra, Juan D., et al.
Publicado: (2025)

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
por: Li, Yucen Lily, et al.
Publicado: (2023)

Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates
por: Polson, Nick, et al.
Publicado: (2026)

Information-Theoretic Safe Bayesian Optimization
por: Bottero, Alessandro G., et al.
Publicado: (2024)

Information-Theoretic Bayesian Optimization for Bilevel Optimization Problems
por: Kanayama, Takuya, et al.
Publicado: (2025)

Information Theoretic Bayesian Optimization over the Probability Simplex
por: Pavesi, Federico, et al.
Publicado: (2026)

A Bayesian Information-Theoretic Approach to Data Attribution
por: Tailor, Dharmesh, et al.
Publicado: (2026)

On the hierarchical Bayesian modelling of frequency response functions
por: Dardeno, T. A., et al.
Publicado: (2023)

Surrogate modeling for Bayesian optimization beyond a single Gaussian process
por: Lu, Qin, et al.
Publicado: (2022)

An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits
por: Gouverneur, Amaury, et al.
Publicado: (2024)

Bayesian Neural Network Surrogates for Bayesian Optimization of Carbon Capture and Storage Operations
por: Fotias, Sofianos Panagiotis, et al.
Publicado: (2025)

Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference
por: Reiser, Philipp, et al.
Publicado: (2023)

Bayesian reversal of the liquid level trajectory in a draining tank for pollution forensics
por: Jones, Kyla D., et al.
Publicado: (2026)

An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces
por: Gouverneur, Amaury, et al.
Publicado: (2025)

Bayesian Optimization of Process Parameters of a Sensor-Based Sorting System using Gaussian Processes as Surrogate Models
por: Kronenwett, Felix, et al.
Publicado: (2025)

Sequential Bayesian Design for Efficient Surrogate Construction in the Inversion of Darcy Flows
por: Wang, Hongji, et al.
Publicado: (2025)

Bayesian Surrogates for Risk-Aware Pre-Assessment of Aging Bridge Portfolios
por: Kuhn, Sophia V., et al.
Publicado: (2025)

One-Stage Top-$k$ Learning-to-Defer: Score-Based Surrogates with Theoretical Guarantees
por: Montreuil, Yannis, et al.
Publicado: (2025)

Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis
por: Jose, Sharu Theresa, et al.
Publicado: (2024)

Gaussian Surrogates for Poisson Imaging: Some Theoretical and Empirical Results
por: Spitzer, Alexandra, et al.
Publicado: (2026)

Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation
por: Taylor, Ian, et al.
Publicado: (2025)

Bayesian Surrogate Training on Multiple Data Sources: A Hybrid Modeling Strategy
por: Reiser, Philipp, et al.
Publicado: (2024)

Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
por: Jaber, Edgar, et al.
Publicado: (2024)

Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
por: Niu, Ruijia, et al.
Publicado: (2024)

Scaling Up Bayesian DAG Sampling
por: Nikzad, Daniele, et al.
Publicado: (2025)

Unifying Information-Theoretic and Pair-Counting Clustering Similarity
por: Gates, Alexander J.
Publicado: (2025)

Uncertainty-Aware Surrogate-based Amortized Bayesian Inference for Computationally Expensive Models
por: Scheurer, Stefania, et al.
Publicado: (2025)

Information Theoretic Lower Bounds for Information Theoretic Upper Bounds
por: Livni, Roi
Publicado: (2023)

On the Information Processing of One-Dimensional Wasserstein Distances with Finite Samples
por: Jang, Cheongjae, et al.
Publicado: (2025)

Clustering-based Meta Bayesian Optimization with Theoretical Guarantee
por: Nguyen, Khoa, et al.
Publicado: (2025)

Open-Source High-Speed Flight Surrogate Modeling Framework
por: Korenyi-Both, Tyler E., et al.
Publicado: (2024)

Deep Intrinsic Coregionalization Multi-Output Gaussian Process Surrogate with Active Learning
por: Chang, Chun-Yi, et al.
Publicado: (2025)

On Approaches to Building Surrogate ODE Models for Diffusion Bridges
por: Khilchuk, Maria, et al.
Publicado: (2025)

Missing Data Multiple Imputation for Tabular Q-Learning in Online RL
por: Chasalow, Kyla, et al.
Publicado: (2025)

Deep Learning Surrogates for Real-Time Gas Emission Inversion
por: Newman, Thomas, et al.
Publicado: (2025)

Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI
por: Ji, Wenlong, et al.
Publicado: (2025)

Attention-Informed Surrogates for Navigating Power-Performance Trade-offs in HPC
por: Ahmed, Ashna Nawar, et al.
Publicado: (2026)