J. Scott Hosking

According to our database, J. Scott Hosking authored at least 9 papers between 2020 and 2024.

Collaborative distances:

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

2024

Sea ice detection using concurrent multispectral and synthetic aperture radar imagery.

Martin S. J. Rogers, Maria Fox, Andrew Fleming, Louisa van Zeeland, Jeremy Wilkinson, J. Scott Hosking

CoRR, 2024

2023

Autoregressive Conditional Neural Processes.

Wessel P. Bruinsma, Stratis Markou, James Requeima, Andrew Y. K. Foong, Tom R. Andersson, Anna Vaughan, Anthony Buonomo, J. Scott Hosking, Richard E. Turner

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Active Learning with Convolutional Gaussian Neural Processes for Environmental Sensor Placement.

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

CoRR, 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

Kernel Learning for Explainable Climate Science.

Vidhi Lalchand, Kenza Tazi, Talay M. Cheema, Richard E. Turner, J. Scott Hosking

CoRR, 2022

Stochastic Parameterizations: Better Modelling of Temporal Correlations using Probabilistic Machine Learning.

Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, Damon J. Wischik

CoRR, 2022

2021

Convolutional conditional neural processes for local climate downscaling.

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

CoRR, 2021

2020

Ensembling geophysical models with Bayesian Neural Networks.

Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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