François-Xavier Briol

61 papers A* 14A 6Journal 37Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Amortised and provably-robust simulation-based inference. CoRR Ayush Bharti, Charita Dellaporta, Yuga Hikida, François-Xavier Briol
2025	—	`conf`	A Dictionary of Closed-Form Kernel Mean Embeddings. ProbNum François-Xavier Briol, Toni Karvonen, Alexandra Gessner, Maren Mahsereci
2025	J	`jnl`	A Dictionary of Closed-Form Kernel Mean Embeddings. CoRR François-Xavier Briol, Alexandra Gessner, Toni Karvonen, Maren Mahsereci
2025	J	`jnl`	BayesSum: Bayesian Quadrature in Discrete Spaces. CoRR Sophia Seulkee Kang, François-Xavier Briol, Toni Karvonen, Zonghao Chen
2025	J	`jnl`	Composite Goodness-of-fit Tests with Kernels. J. Mach. Learn. Res. Oscar Key, Arthur Gretton, François-Xavier Briol, Tamara Fernandez
2025	A	`conf`	Cost-aware simulation-based inference. AISTATS Ayush Bharti, Daolang Huang, Samuel Kaski, François-Xavier Briol
2025	A*	`conf`	Kernel Quantile Embeddings and Associated Probability Metrics. ICML Masha Naslidnyk, Siu Lun Chau, François-Xavier Briol, Krikamol Muandet
2025	J	`jnl`	Kernel Quantile Embeddings and Associated Probability Metrics. CoRR Masha Naslidnyk, Siu Lun Chau, François-Xavier Briol, Krikamol Muandet
2025	J	`jnl`	Multi-Output Robust and Conjugate Gaussian Processes. CoRR Joshua Rooijakkers, Leiv Rønneberg, François-Xavier Briol, Jeremias Knoblauch, Matías Altamirano
2025	J	`jnl`	Multilevel neural simulation-based inference. CoRR Yuga Hikida, Ayush Bharti, Niall Jeffrey, François-Xavier Briol
2025	A*	`conf`	Nested Expectations with Kernel Quadrature. ICML Zonghao Chen, Masha Naslidnyk, François-Xavier Briol
2025	J	`jnl`	Nested Expectations with Kernel Quadrature. CoRR Zonghao Chen, Masha Naslidnyk, François-Xavier Briol
2025	J	`jnl`	On the Robustness of Kernel Goodness-of-Fit Tests. J. Mach. Learn. Res. Xing Liu, François-Xavier Briol
2025	A*	`conf`	Robust and Conjugate Spatio-Temporal Gaussian Processes. ICML William Laplante, Matías Altamirano, Andrew B. Duncan, Jeremias Knoblauch, François-Xavier Briol
2025	J	`jnl`	Stationary MMD Points for Cubature. CoRR Zonghao Chen, Toni Karvonen, Heishiro Kanagawa, François-Xavier Briol, Chris J. Oates
2024	A	`conf`	Conditional Bayesian Quadrature. UAI Zonghao Chen, Masha Naslidnyk, Arthur Gretton, François-Xavier Briol
2024	J	`jnl`	Conditional Bayesian Quadrature. CoRR Zonghao Chen, Masha Naslidnyk, Arthur Gretton, François-Xavier Briol
2024	J	`jnl`	Cost-aware Simulation-based Inference. CoRR Ayush Bharti, Daolang Huang, Samuel Kaski, François-Xavier Briol
2024	J	`jnl`	On the Robustness of Kernel Goodness-of-Fit Tests. CoRR Xing Liu, François-Xavier Briol
2024	A*	`conf`	Outlier-robust Kalman Filtering through Generalised Bayes. ICML Gerardo Duran-Martin, Matías Altamirano, Alexander Y. Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier Briol, Kevin Patrick Murphy
2024	J	`jnl`	Outlier-robust Kalman Filtering through Generalised Bayes. CoRR Gerardo Duran-Martin, Matías Altamirano, Alexander Y. Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier Briol, Kevin Murphy
2024	A*	`conf`	Robust and Conjugate Gaussian Process Regression. ICML Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
2023	J	`jnl`	Bayesian Numerical Integration with Neural Networks. CoRR Katharina Ott, Michael Tiemann, Philipp Hennig, François-Xavier Briol
2023	A	`conf`	Baysian numerical integration with neural networks. UAI Katharina Ott, Michael Tiemann, Philipp Hennig, François-Xavier Briol
2023	A	`conf`	Meta-learning Control Variates: Variance Reduction with Limited Data. UAI Zhuo Sun, Chris J. Oates, François-Xavier Briol
2023	J	`jnl`	Meta-learning Control Variates: Variance Reduction with Limited Data. CoRR Zhuo Sun, Chris J. Oates, François-Xavier Briol
2023	A	`conf`	Multilevel Bayesian Quadrature. AISTATS Kaiyu Li, Daniel Giles, Toni Karvonen, Serge Guillas, François-Xavier Briol
2023	A*	`conf`	Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. ICML Ayush Bharti, Masha Naslidnyk, Oscar Key, Samuel Kaski, François-Xavier Briol
2023	J	`jnl`	Robust and Conjugate Gaussian Process Regression. CoRR Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
2023	A*	`conf`	Robust and Scalable Bayesian Online Changepoint Detection. ICML Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
2023	J	`jnl`	Robust and Scalable Bayesian Online Changepoint Detection. CoRR Matías Altamirano, François-Xavier Briol, Jeremias Knoblauch
2023	A*	`conf`	Vector-Valued Control Variates. ICML Zhuo Sun, Alessandro Barp, François-Xavier Briol
2022	A	`conf`	Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. AISTATS Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
2022	J	`jnl`	Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap. CoRR Charita Dellaporta, Jeremias Knoblauch, Theodoros Damoulas, François-Xavier Briol
2022	J	`jnl`	Towards Healing the Blindness of Score Matching. CoRR Mingtian Zhang, Oscar Key, Peter Hayes, David Barber, Brooks Paige, François-Xavier Briol
2021	J	`jnl`	Composite Goodness-of-fit Tests with Kernels. CoRR Oscar Key, Tamara Fernandez, Arthur Gretton, François-Xavier Briol
2021	J	`jnl`	Convergence Guarantees for Gaussian Process Means With Misspecified Likelihoods and Smoothness. J. Mach. Learn. Res. George Wynne, François-Xavier Briol, Mark Girolami
2021	J	`jnl`	ProbNum: Probabilistic Numerics in Python. CoRR Jonathan Wenger, Nicholas Krämer, Marvin Pförtner, Jonathan Schmidt, Nathanael Bosch, Nina Effenberger, Johannes Zenn, Alexandra Gessner, Toni Karvonen, François-Xavier Briol, Maren Mahsereci, Philipp Hennig
2021	J	`jnl`	The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks. J. Mach. Learn. Res. Takuo Matsubara, Chris J. Oates, François-Xavier Briol
2020	A*	`conf`	Bayesian Probabilistic Numerical Integration with Tree-Based Models. NeurIPS Harrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth R. Flaxman, François-Xavier Briol
2020	J	`jnl`	Bayesian Probabilistic Numerical Integration with Tree-Based Models. CoRR Harrison Zhu, Xing Liu, Ruya Kang, Zhichao Shen, Seth R. Flaxman, François-Xavier Briol
2020	J	`jnl`	Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models. CoRR George Wynne, François-Xavier Briol, Mark A. Girolami
2020	—	`conf`	Scalable Control Variates for Monte Carlo Methods Via Stochastic Optimization. MCQMC Shijing Si, Chris J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol
2020	J	`jnl`	Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization. CoRR Shijing Si, Chris J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol
2020	J	`jnl`	The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks. CoRR Takuo Matsubara, Chris J. Oates, François-Xavier Briol
2019	J	`jnl`	Contributed Discussion of "A Bayesian Conjugate Gradient Method". CoRR François-Xavier Briol, Francisco Alejandro DiazDelaO, Peter O. Hristov
2019	A*	`conf`	Minimum Stein Discrepancy Estimators. NeurIPS Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey
2019	J	`jnl`	Minimum Stein Discrepancy Estimators. CoRR Alessandro Barp, François-Xavier Briol, Andrew B. Duncan, Mark A. Girolami, Lester W. Mackey
2019	J	`jnl`	Statistical Inference for Generative Models with Maximum Mean Discrepancy. CoRR François-Xavier Briol, Alessandro Barp, Andrew B. Duncan, Mark A. Girolami
2019	A*	`conf`	Stein Point Markov Chain Monte Carlo. ICML Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark A. Girolami, Lester W. Mackey, Chris J. Oates
2018	A*	`conf`	Bayesian Quadrature for Multiple Related Integrals. ICML Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami
2018	J	`jnl`	Bayesian Quadrature for Multiple Related Integrals. CoRR Xiaoyue Xi, François-Xavier Briol, Mark A. Girolami
2018	J	`jnl`	Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?". CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic
2018	A*	`conf`	Stein Points. ICML Wilson Ye Chen, Lester W. Mackey, Jackson Gorham, François-Xavier Briol, Chris J. Oates
2018	J	`jnl`	Stein Points. CoRR Wilson Ye Chen, Lester W. Mackey, Jackson Gorham, François-Xavier Briol, Chris J. Oates
2017	J	`jnl`	Geometry and Dynamics for Markov Chain Monte Carlo. CoRR Alessandro Barp, François-Xavier Briol, Anthony D. Kennedy, Mark A. Girolami
2017	A*	`conf`	On the Sampling Problem for Kernel Quadrature. ICML François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami
2017	J	`jnl`	On the Sampling Problem for Kernel Quadrature. CoRR François-Xavier Briol, Chris J. Oates, Jon Cockayne, Wilson Ye Chen, Mark A. Girolami
2017	—	`conf`	Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models. NIPS Chris J. Oates, Steven A. Niederer, Angela W. C. Lee, François-Xavier Briol, Mark A. Girolami
2015	—	`conf`	Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. NIPS François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne
2015	J	`jnl`	Probabilistic Integration. CoRR François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic