Cover Image

Indirect Query Bayesian Optimization with Integrated Feedback

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Mengyan, Bouabid, Shahine, Ong, Cheng Soon, Flaxman, Seth, Sejdinovic, Dino
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation
by: Bouabid, Shahine, et al.
Published: (2023)

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families
by: Tsuchida, Russell, et al.
Published: (2024)

Squared families: Searching beyond regular probability models
by: Tsuchida, Russell, et al.
Published: (2025)

Graph Agnostic Causal Bayesian Optimisation
by: Mukherjee, Sumantrak, et al.
Published: (2024)

An Overview of Causal Inference using Kernel Embeddings
by: Sejdinovic, Dino
Published: (2024)

Score-based generative emulation of impact-relevant Earth system model outputs
by: Bouabid, Shahine, et al.
Published: (2025)

Domain Generalisation via Imprecise Learning
by: Singh, Anurag, et al.
Published: (2024)

All Models Are Miscalibrated, But Some Less So: Comparing Calibration with Conditional Mean Operators
by: Moskvichev, Peter, et al.
Published: (2025)

ActiveCQ: Active Estimation of Causal Quantities
by: Gao, Erdun, et al.
Published: (2025)

Near-Optimal Approximations for Bayesian Inference in Function Space
by: Wild, Veit, et al.
Published: (2025)

Bayesian Adaptive Calibration and Optimal Design
by: Oliveira, Rafael, et al.
Published: (2024)

Label Distribution Learning using the Squared Neural Family on the Probability Simplex
by: Zhang, Daokun, et al.
Published: (2024)

Transformer Neural Processes - Kernel Regression
by: Jenson, Daniel, et al.
Published: (2024)

Neural-Kernel Conditional Mean Embeddings
by: Shimizu, Eiki, et al.
Published: (2024)

Causal-EPIG: A Prediction-Oriented Active Learning Framework for CATE Estimation
by: Gao, Erdun, et al.
Published: (2025)

Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes
by: Jenson, Daniel, et al.
Published: (2025)

The Generalised Kernel Covariance Measure
by: Bergen, Luca, et al.
Published: (2026)

Measuring Differences between Conditional Distributions using Kernel Embeddings
by: Moskvichev, Peter, et al.
Published: (2026)

Co-Learning Bayesian Optimization
by: Guo, Zhendong, et al.
Published: (2025)

A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment
by: Hu, Robert, et al.
Published: (2021)

Generalization Certificates for Adversarially Robust Bayesian Linear Regression
by: Sabanayagam, Mahalakshmi, et al.
Published: (2025)

Instrumental and Proximal Causal Inference with Gaussian Processes
by: Zhang, Yuqi, et al.
Published: (2026)

DeepRV: Accelerating Spatiotemporal Inference with Pre-trained Neural Priors
by: Navott, Jhonathan, et al.
Published: (2025)

Credal Two-Sample Tests of Epistemic Uncertainty
by: Chau, Siu Lun, et al.
Published: (2024)

Tokenised Flow Matching for Hierarchical Simulation Based Inference
by: Charles, Giovanni, et al.
Published: (2026)

Gaussian Processes and Reproducing Kernels: Connections and Equivalences
by: Kanagawa, Motonobu, et al.
Published: (2025)

Graphon Mixtures
by: Kandanaarachchi, Sevvandi, et al.
Published: (2025)

Uncertain Multi-Objective Recommendation via Orthogonal Meta-Learning Enhanced Bayesian Optimization
by: Wang, Hongxu, et al.
Published: (2025)

Graphons of Line Graphs
by: Kandanaarachchi, Sevvandi, et al.
Published: (2024)

Giga-scale Kernel Matrix Vector Multiplication on GPU
by: Hu, Robert, et al.
Published: (2022)

Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation
by: Tan, Kim Yong, et al.
Published: (2025)

Observationally Informed Adaptive Causal Experimental Design
by: Gao, Erdun, et al.
Published: (2026)

A pseudo-inverse of a line graph
by: Kandanaarachchi, Sevvandi, et al.
Published: (2025)

Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field
by: Tan, Kim Yong, et al.
Published: (2026)

Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks
by: Doan, Bao Gia, et al.
Published: (2024)

Adversarial Query Synthesis via Bayesian Optimization
by: Tao, Jeffrey, et al.
Published: (2026)

Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles
by: Liu, Shengcai, et al.
Published: (2025)

Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation
by: Lyu, Yueming, et al.
Published: (2024)

IterInject: Indirect Prompt Injection Against LLM Agents via Feedback-Guided Iterative Optimization
by: Chen, Zixuan, et al.
Published: (2026)

EvoSpeak: Large Language Models for Interpretable Genetic Programming-Evolved Heuristics
by: Xu, Meng, et al.
Published: (2025)