William Tebbutt

According to our database, William Tebbutt authored at least 11 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

End-to-end data-driven weather prediction.

Anna Allen, Stratis Markou, Will Tebbutt, James Requeima, Wessel P. Bruinsma, Tom R. Andersson, Michael Herzog, Nicholas D. Lane, Matthew Chantry, J. Scott Hosking, Richard E. Turner

Nat., 2025

2024

Aardvark Weather: end-to-end data-driven weather forecasting.

Anna Vaughan, Stratis Markou, Will Tebbutt, James Requeima, Wessel P. Bruinsma, Tom R. Andersson, Michael Herzog, Nicholas D. Lane, J. Scott Hosking, Richard E. Turner

CoRR, 2024

2022

Ice Core Dating using Probabilistic Programming.

Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite, Will Tebbutt, Richard E. Turner, J. Scott Hosking, Neil D. Lawrence, Markus Kaiser

CoRR, 2022

2021

Convolutional conditional neural processes for local climate downscaling.

Anna Vaughan, William Tebbutt, J. Scott Hosking, Richard E. Turner

CoRR, 2021

Combining pseudo-point and state space approximations for sum-separable Gaussian Processes.

Will Tebbutt, Arno Solin, Richard E. Turner

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Sparse Gaussian Process Variational Autoencoders.

Matthew Ashman, Jonathan So, William Tebbutt, Vincent Fortuin, Michael Pearce, Richard E. Turner

CoRR, 2020

Scalable Exact Inference in Multi-Output Gaussian Processes.

Wessel P. Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner

Proceedings of the 37th International Conference on Machine Learning, 2020

Generalized Physics-Informed Learning through Language-Wide Differentiable Programming.

Christopher Rackauckas, Alan Edelman, Keno Fischer, Mike Innes, Elliot Saba, Viral B. Shah, Will Tebbutt

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020

2019

A Differentiable Programming System to Bridge Machine Learning and Scientific Computing.

Mike Innes, Alan Edelman, Keno Fischer, Christopher Rackauckas, Elliot Saba, Viral B. Shah, Will Tebbutt

CoRR, 2019

The Gaussian Process Autoregressive Regression Model (GPAR).

James Requeima, William Tebbutt, Wessel P. Bruinsma, Richard E. Turner

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

AdvancedHMC.jl: A robust, modular and e cient implementation of advanced HMC algorithms.

Kai Xu, Hong Ge, Will Tebbutt, Mohamed Tarek, Martin Trapp, Zoubin Ghahramani

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019