Jon Cockayne - RankMe

30 papers A* 1A 2Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Calibrated Computation-Aware Gaussian Processes. AISTATS Disha Hegde, Mohamed Adil, Jon Cockayne
2025	A	`conf`	Computation-Aware Kalman Filtering and Smoothing. AISTATS Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig
2025	—	`conf`	Learning to Solve Related Linear Systems. ProbNum Disha Hegde, Jon Cockayne
2025	J	`jnl`	Learning to Solve Related Linear Systems. CoRR Disha Hegde, Jon Cockayne
2025	—	`ed.`	Proceedings of the First International Conference on Probabilistic Numerics (ProbNum 2025), 1-3 September 2025, EURECOM, Sophia Antipolis, France ProbNum Motonobu Kanagawa, Jon Cockayne, Alexandra Gessner, Philipp Hennig
2025	—	`conf`	Randomised Postiterations for Calibrated BayesCG. ProbNum Niall Vyas, Disha Hegde, Jon Cockayne
2025	J	`jnl`	Randomised Postiterations for Calibrated BayesCG. CoRR Niall Vyas, Disha Hegde, Jon Cockayne
2024	J	`jnl`	Calibrated Computation-Aware Gaussian Processes. CoRR Disha Hegde, Mohamed Adil, Jon Cockayne
2024	J	`jnl`	Computation-Aware Kalman Filtering and Smoothing. CoRR Marvin Pförtner, Jonathan Wenger, Jon Cockayne, Philipp Hennig
2023	J	`jnl`	A probabilistic Taylor expansion with Gaussian processes. Trans. Mach. Learn. Res. Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
2023	J	`jnl`	Statistical properties of BayesCG under the Krylov prior. Numerische Mathematik Tim W. Reid, Ilse C. F. Ipsen, Jon Cockayne, Chris J. Oates
2023	J	`jnl`	Theoretical Guarantees for the Statistical Finite Element Method. SIAM/ASA J. Uncertain. Quantification Yanni Papandreou, Jon Cockayne, Mark Girolami, Andrew B. Duncan
2022	J	`jnl`	Statistical Properties of the Probabilistic Numeric Linear Solver BayesCG. CoRR Tim W. Reid, Ilse C. F. Ipsen, Jon Cockayne, Chris J. Oates
2022	J	`jnl`	Testing Whether a Learning Procedure is Calibrated. J. Mach. Learn. Res. Jon Cockayne, Matthew M. Graham, Chris J. Oates, Timothy John Sullivan, Onur Teymur
2021	J	`jnl`	A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations. CoRR Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
2021	J	`jnl`	Bayesian Numerical Methods for Nonlinear Partial Differential Equations. CoRR Junyang Wang, Jon Cockayne, Oksana A. Chkrebtii, Timothy John Sullivan, Chris J. Oates
2021	J	`jnl`	Bayesian numerical methods for nonlinear partial differential equations. Stat. Comput. Junyang Wang, Jon Cockayne, Oksana A. Chkrebtii, Timothy John Sullivan, Chris J. Oates
2021	J	`jnl`	Probabilistic Iterative Methods for Linear Systems. J. Mach. Learn. Res. Jon Cockayne, Ilse C. F. Ipsen, Chris J. Oates, Tim W. Reid
2021	J	`jnl`	Theoretical Guarantees for the Statistical Finite Element Method. CoRR Yanni Papandreou, Jon Cockayne, Mark Girolami, Andrew B. Duncan
2020	J	`jnl`	A Probabilistic Numerical Extension of the Conjugate Gradient Method. CoRR Tim W. Reid, Ilse C. F. Ipsen, Jon Cockayne, Chris J. Oates
2020	J	`jnl`	Probabilistic Gradients for Fast Calibration of Differential Equation Models. CoRR Jon Cockayne, Andrew B. Duncan
2020	J	`jnl`	Probabilistic Iterative Methods for Linear Systems. CoRR Jon Cockayne, Ilse C. F. Ipsen, Chris J. Oates, Tim W. Reid
2019	J	`jnl`	Bayesian Probabilistic Numerical Methods. SIAM Rev. Jon Cockayne, Chris J. Oates, Timothy John Sullivan, Mark A. Girolami
2019	J	`jnl`	Probabilistic linear solvers: a unifying view. Stat. Comput. Simon Bartels, Jon Cockayne, Ilse C. F. Ipsen, Philipp Hennig
2018	J	`jnl`	A Bayesian Conjugate Gradient Method. CoRR Jon Cockayne, Chris J. Oates, Mark A. Girolami
2017	J	`jnl`	Bayesian Probabilistic Numerical Methods. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, 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	J	`jnl`	Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami
2016	J	`jnl`	Probabilistic Meshless Methods for Partial Differential Equations and Bayesian Inverse Problems. CoRR Jon Cockayne, Chris J. Oates, Tim Sullivan, Mark A. Girolami