← Authors

François-Xavier Briol

26 papers · 2015–2025 · 5 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) 🗺️ Taxonomy Completionist (26) 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🏃 Academic Marathon (10) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (14) 🏆 Keyword Champion (2) 🔥 Unstoppable (9) 💎 Century Club (26) ⚡ Prolific Year (6) 🗃️ Keyword Collector (76)

Conferences

ICML (12) JMLR (4) NIPS (4) AISTATS (3) UAI (3)

Top co-authors

Mark Girolami (7) Jeremias Knoblauch (5) Chris Oates (4) Masha Naslidnyk (4) Matias Altamirano (4) Wilson Ye Chen (3) Alessandro Barp (3) Lester Mackey (3) Zhuo Sun (2) Zonghao Chen (2)

Research topics

Statistics (2)

Keywords

numerical integration (5) bayesian quadrature (5) bayesian inference (5) kernel methods (4) gaussian process (4) stein discrepancy (3) maximum mean discrepancy (3) variance reduction (2) posterior distribution (2) markov chain monte carlo (2) monte carlo estimator (2) control variate (2) hypothesis testing (2) uncertainty quantification (2) bayesian neural network (2) kernel stein discrepancy (2) importance sampling (1) laplace approximation (1) parameter estimation (1) probabilistic modeling (1)

Papers

Nested Expectations with Kernel Quadrature ICML 2025
Kernel Quantile Embeddings and Associated Probability Metrics ICML 2025
Cost-aware simulation-based inference AISTATS 2025
Robust and Conjugate Spatio-Temporal Gaussian Processes ICML 2025
On the Robustness of Kernel Goodness-of-Fit Tests JMLR 2025
Composite Goodness-of-fit Tests with Kernels JMLR 2025
Robust and Conjugate Gaussian Process Regression ICML 2024
Outlier-robust Kalman Filtering through Generalised Bayes ICML 2024
Conditional Bayesian Quadrature UAI 2024
Vector-Valued Control Variates ICML 2023
Multilevel Bayesian Quadrature AISTATS 2023
Robust and Scalable Bayesian Online Changepoint Detection ICML 2023
Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference ICML 2023
Bayesian numerical integration with neural networks UAI 2023
Meta-learning Control Variates: Variance Reduction with Limited Data UAI 2023
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap AISTATS 2022
Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness JMLR 2021
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021
Bayesian Probabilistic Numerical Integration with Tree-Based Models NIPS 2020
Stein Point Markov Chain Monte Carlo ICML 2019
Minimum Stein Discrepancy Estimators NIPS 2019
Stein Points ICML 2018
Bayesian Quadrature for Multiple Related Integrals ICML 2018
Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NIPS 2017
On the Sampling Problem for Kernel Quadrature ICML 2017
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees NIPS 2015