François-Xavier Briol
26 papers · 2015–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (10) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (14)
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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
Research topics
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