J. Scott Hosking

16 papers A* 3Journal 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	End-to-end data-driven weather prediction. Nat. 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
2025	J	`jnl`	FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design. CoRR Tom Dunstan, Oliver Strickson, Thusal Bennett, Jack Bowyer, Matthew Burnand, James Chappell, Alejandro Coca-Castro, Kirstine Ida Dale, Eric G. Daub, Noushin Eftekhari, Manvendra Janmaijaya, Jon Lillis, David Salvador Jasin, Nathan Simpson, Ryan Sze-Yin Chan, Mohamad Elmasri, Lydia Allegranza France, Sam Madge, Levan Bokeria, Hannah Brown, Tom Dodds, Anna-Louise Ellis, David Llewellyn-Jones, Theo McCaie, Sophia Moreton, Tom Potter, James Robinson, Adam A. Scaife, Iain Stenson, David Walters, Karina Bett-Williams, Louisa van Zeeland, Peter Yatsyshin, J. Scott Hosking
2024	J	`jnl`	Aardvark Weather: end-to-end data-driven weather forecasting. CoRR 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
2024	J	`jnl`	Defining error accumulation in ML atmospheric simulators. CoRR Raghul Parthipan, Mohit Anand, Hannah M. Christensen, J. Scott Hosking, Damon J. Wischik
2024	J	`jnl`	Sea ice detection using concurrent multispectral and synthetic aperture radar imagery. CoRR Martin S. J. Rogers, Maria Fox, Andrew Fleming, Louisa van Zeeland, Jeremy Wilkinson, J. Scott Hosking
2023	A*	`conf`	Autoregressive Conditional Neural Processes. ICLR Wessel P. Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom R. Andersson, Anna Vaughan, Anthony Buonomo, J. Scott Hosking, Richard E. Turner
2023	J	`jnl`	Autoregressive Conditional Neural Processes. CoRR Wessel P. Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom R. Andersson, Anna Vaughan, Anthony Buonomo, J. Scott Hosking, Richard E. Turner
2022	J	`jnl`	Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement. CoRR Tom R. Andersson, Wessel P. Bruinsma, Stratis Markou, James Requeima, Alejandro Coca-Castro, Anna Vaughan, Anna-Louise Ellis, Matthew Lazzara, Daniel C. Jones, J. Scott Hosking, Richard E. Turner
2022	J	`jnl`	Ice Core Dating using Probabilistic Programming. CoRR Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite, Will Tebbutt, Richard E. Turner, J. Scott Hosking, Neil D. Lawrence, Markus Kaiser
2022	J	`jnl`	Kernel Learning for Explainable Climate Science. CoRR Vidhi Lalchand, Kenza Tazi, Talay M. Cheema, Richard E. Turner, J. Scott Hosking
2022	J	`jnl`	Stochastic Parameterizations: Better Modelling of Temporal Correlations using Probabilistic Machine Learning. CoRR Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, Damon J. Wischik
2021	J	`jnl`	Convolutional conditional neural processes for local climate downscaling. CoRR Anna Vaughan, William Tebbutt, J. Scott Hosking, Richard E. Turner
2020	A*	`conf`	Ensembling geophysical models with Bayesian Neural Networks. NeurIPS Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
2020	J	`jnl`	Ensembling geophysical models with Bayesian Neural Networks. CoRR Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
2020	A*	`conf`	Scalable Exact Inference in Multi-Output Gaussian Processes. ICML Wessel P. Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner
2019	J	`jnl`	Scalable Exact Inference in Multi-Output Gaussian Processes. CoRR Wessel P. Bruinsma, Eric Perim, William Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner