Duncan Watson-Parris

According to our database, Duncan Watson-Parris authored at least 16 papers between 2019 and 2024.

Collaborative distances:

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

2024

Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.

Ruijia Niu, Dongxia Wu, Kai Kim, Yi-An Ma, Duncan Watson-Parris, Rose Yu

CoRR, 2024

CloudTracks: A Dataset for Localizing Ship Tracks in Satellite Images of Clouds.

Muhammad Ahmed Chaudhry, Lyna Kim, Jeremy Irvin, Yuzu Ido, Sonia Chu, Jared Thomas Isobe, Andrew Y. Ng, Duncan Watson-Parris

CoRR, 2024

2022

Building high accuracy emulators for scientific simulations with deep neural architecture search.

Muhammad Firmansyah Kasim, Duncan Watson-Parris, Lucia Deaconu, Sophy Oliver, Peter W. Hatfield, Dustin H. Froula, Gianluca Gregori, Matt Jarvis, Samar Khatiwala, Jun Korenaga, Jacob Topp-Mugglestone, Eleonora Viezzer, Sam M. Vinko

Mach. Learn. Sci. Technol., 2022

Exploring Randomly Wired Neural Networks for Climate Model Emulation.

William Yik, Sam J. Silva, Andrew Geiss, Duncan Watson-Parris

CoRR, 2022

Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds.

Kenza Tazi, Emiliano Díaz Salas-Porras, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert

CoRR, 2022

Identifying the Causes of Pyrocumulonimbus (PyroCb).

Emiliano Díaz Salas-Porras, Kenza Tazi, Ashwin Braude, Daniel Okoh, Kara D. Lamb, Duncan Watson-Parris, Paula Harder, Nis Meinert

CoRR, 2022

Physics-Informed Learning of Aerosol Microphysics.

Paula Harder, Duncan Watson-Parris, Philip Stier, Dominik Strassel, Nicolas R. Gauger, Janis Keuper

CoRR, 2022

2021

Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific.

Andrew Jesson, Peter Manshausen, Alyson Douglas, Duncan Watson-Parris, Yarin Gal, Philip Stier

CoRR, 2021

Emulating Aerosol Microphysics with Machine Learning.

Paula Harder, Duncan Watson-Parris, Dominik Strassel, Nicolas R. Gauger, Philip Stier, Janis Keuper

CoRR, 2021

RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

RainBench: Towards Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

CoRR, 2020

NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations.

Paula Harder, William K. Jones, Redouane Lguensat, Shahine Bouabid, James Fulton, Dánell Quesada-Chacón, Aris Marcolongo, Sofija Stefanovic, Yuhan Rao, Peter Manshausen, Duncan Watson-Parris

CoRR, 2020

Up to two billion times acceleration of scientific simulations with deep neural architecture search.

Muhammad Firmansyah Kasim, Duncan Watson-Parris, Lucia Deaconu, Sophy Oliver, Peter W. Hatfield, Dustin H. Froula, Gianluca Gregori, Matt Jarvis, Samar Khatiwala, Jun Korenaga, Jacob Topp-Mugglestone, Eleonora Viezzer, Sam M. Vinko

CoRR, 2020

The 2020 Climate Informatics Hackathon: Generating Nighttime Satellite Imagery from Infrared Observations.

William K. Jones, Redouane Lguensat, Anastase Alexandre Charantonis, Duncan Watson-Parris

Proceedings of the CI 2020: 10th International Conference on Climate Informatics, 2020

2019

Detecting anthropogenic cloud perturbations with deep learning.

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony L. Caterini, Dino Sejdinovic, Philip Stier

CoRR, 2019

Cumulo: A Dataset for Learning Cloud Classes.

Valentina Zantedeschi, Fabrizio Falasca, Alyson Douglas, Richard Strange, Matt J. Kusner, Duncan Watson-Parris

CoRR, 2019