Cover Image

Conditional Bayesian Quadrature

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Zonghao, Naslidnyk, Masha, Gretton, Arthur, Briol, François-Xavier
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Nested Expectations with Kernel Quadrature
by: Chen, Zonghao, et al.
Published: (2025)

BayesSum: Bayesian Quadrature in Discrete Spaces
by: Kang, Sophia Seulkee, et al.
Published: (2025)

Kernel Quantile Embeddings and Associated Probability Metrics
by: Naslidnyk, Masha, et al.
Published: (2025)

Scalable Kernel-Based Distances for Statistical Inference and Integration
by: Naslidnyk, Masha
Published: (2026)

Composite Goodness-of-fit Tests with Kernels
by: Key, Oscar, et al.
Published: (2021)

Thinned Mean Field Langevin Dynamics
by: Chen, Zonghao, et al.
Published: (2026)

Stationary MMD Points
by: Chen, Zonghao, et al.
Published: (2025)

Towards a Unified Analysis of Neural Networks in Nonparametric Instrumental Variable Regression: Optimization and Generalization
by: Chen, Zonghao, et al.
Published: (2025)

Cost-aware simulation-based inference
by: Bharti, Ayush, et al.
Published: (2024)

Sobolev Regularized MMD Gradient Flow
by: Tian, Chenyang, et al.
Published: (2026)

Amortised and provably-robust simulation-based inference
by: Bharti, Ayush, et al.
Published: (2026)

On the Robustness of Kernel Goodness-of-Fit Tests
by: Liu, Xing, et al.
Published: (2024)

A Dictionary of Closed-Form Kernel Mean Embeddings
by: Briol, François-Xavier, et al.
Published: (2025)

Robust and Conjugate Gaussian Process Regression
by: Altamirano, Matias, et al.
Published: (2023)

Robust and Conjugate Spatio-Temporal Gaussian Processes
by: Laplante, William, et al.
Published: (2025)

Multilevel neural simulation-based inference
by: Hikida, Yuga, et al.
Published: (2025)

Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
by: Li, Chengkun, et al.
Published: (2023)

(De)-regularized Maximum Mean Discrepancy Gradient Flow
by: Chen, Zonghao, et al.
Published: (2024)

Nonparametric Instrumental Variable Regression with Observed Covariates
by: Shen, Zikai, et al.
Published: (2025)

Controlling Moments with Kernel Stein Discrepancies
by: Kanagawa, Heishiro, et al.
Published: (2022)

Kernel Single Proxy Control for Deterministic Confounding
by: Xu, Liyuan, et al.
Published: (2023)

Perturbative methods for non-parametric instrumental variable
by: Bu, Wei, et al.
Published: (2026)

Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
by: Zenati, Houssam, et al.
Published: (2026)

Conservative neural posterior estimation via distributionally robust training
by: Laplante, William, et al.
Published: (2026)

Multi-Output Robust and Conjugate Gaussian Processes
by: Rooijakkers, Joshua, et al.
Published: (2025)

Practical Kernel Tests of Conditional Independence
by: Pogodin, Roman, et al.
Published: (2024)

Conformal Prediction as Bayesian Quadrature
by: Snell, Jake C., et al.
Published: (2025)

Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
by: Zenati, Houssam, et al.
Published: (2025)

Regularized $f$-Divergence Kernel Tests
by: Ribero, Mónica, et al.
Published: (2026)

Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
by: Xu, Liyuan, et al.
Published: (2021)

Bayesian Quadrature: Gaussian Processes for Integration
by: Mahsereci, Maren, et al.
Published: (2026)

Towards Healing the Blindness of Score Matching
by: Zhang, Mingtian, et al.
Published: (2022)

Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization
by: Cai, Xu, et al.
Published: (2024)

Interventional Processes for Causal Uncertainty Quantification
by: Dance, Hugh, et al.
Published: (2024)

Kernel Treatment Effects with Adaptively Collected Data
by: Zenati, Houssam, et al.
Published: (2025)

On the Hardness of Conditional Independence Testing In Practice
by: He, Zheng, et al.
Published: (2025)

Near-Optimality of Contrastive Divergence Algorithms
by: Glaser, Pierre, et al.
Published: (2025)

Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves
by: Singh, Rahul, et al.
Published: (2021)

The Illusion of Intervention: Your LLM-Simulated Experiment is an Observational Study
by: Lin, Victoria, et al.
Published: (2026)

Nonparametric Instrumental Regression via Kernel Methods is Minimax Optimal
by: Meunier, Dimitri, et al.
Published: (2024)