Duncan Watson-Parris

According to our database, Duncan Watson-Parris authored at least 30 papers between 2019 and 2026.

Collaborative distances:

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

2026

Wavelet Flow Matching for Multi-Scale Physics Emulation.

Gabriele Accarino, Juan Nathaniel, Carla Roesch, Pierre Gentine, Sara Shamekh, Duncan Watson-Parris, Viviana Acquaviva

CoRR, May, 2026

U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster.

Salva Rühling Cachay, Duncan Watson-Parris, Rose Yu

CoRR, April, 2026

2025

Forecasting Occupational Survivability of Rickshaw Pullers in a Changing Climate with Wearable Data.

Masfiqur Rahaman, Maoyejatun Hasana, Shahad Shahriar Rahman, Md Sajid Mostafiz Noor, Razin Reaz Abedin, Md Toki Tahmid, Duncan Watson-Parris, Tanzeem Choudhury, A. B. M. Alim Al Islam, Tauhidur Rahman

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., December, 2025

WaveSim: A Wavelet-based Multi-scale Similarity Metric for Weather and Climate Fields.

Gabriele Accarino, Viviana Acquaviva, Sara Shamekh, Duncan Watson-Parris, David Lawrence

CoRR, December, 2025

Spatiotemporal Pyramid Flow Matching for Climate Emulation.

Jeremy Andrew Irvin, Jiaqi Han, Zikui Wang, Abdulaziz Alharbi, Yufei Zhao, Nomin-Erdene Bayarsaikhan, Daniele Visioni, Andrew Y. Ng, Duncan Watson-Parris

CoRR, December, 2025

Zephyrus: An Agentic Framework for Weather Science.

Sumanth Varambally, Marshall Fisher, Jas Thakker, Yiwei Chen, Zhirui Xia, Yasaman Jafari, Ruijia Niu, Manas Jain, Veeramakali Vignesh Manivannan, Zachary Novack, Luyu Han, Srikar Eranky, Salva Rühling Cachay, Taylor Berg-Kirkpatrick, Duncan Watson-Parris, Yi-An Ma, Rose Yu

CoRR, October, 2025

Discovering Latent Causal Graphs from Spatiotemporal Data.

Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yian Ma, Rose Yu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Adapting While Learning: Grounding LLMs for Scientific Problems with Tool Usage Adaptation.

Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick, Rose Yu

Proceedings of the Forty-second International Conference on Machine Learning, 2025

ClimaQA: An Automated Evaluation Framework for Climate Question Answering Models.

Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Discovering Latent Structural Causal Models from Spatio-Temporal Data.

Kun Wang, Sumanth Varambally, Duncan Watson-Parris, Yi-An Ma, Rose Yu

CoRR, 2024

Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation.

Bohan Lyu, Yadi Cao, Duncan Watson-Parris, Leon Bergen, Taylor Berg-Kirkpatrick, Rose Yu

CoRR, 2024

ClimaQA: An Automated Evaluation Framework for Climate Foundation Models.

Veeramakali Vignesh Manivannan, Yasaman Jafari, Srikar Eranky, Spencer Ho, Rose Yu, Duncan Watson-Parris, Yian Ma, Leon Bergen, Taylor Berg-Kirkpatrick

CoRR, 2024

Harnessing AI data-driven global weather models for climate attribution: An analysis of the 2017 Oroville Dam extreme atmospheric river.

Jorge Baño-Medina, Agniv Sengupta, Allison Michaelis, Luca Delle Monache, Julie Kalansky, Duncan Watson-Parris

CoRR, 2024

The impact of internal variability on benchmarking deep learning climate emulators.

Björn Lütjens, Raffaele Ferrari, Duncan Watson-Parris, Noelle Selin

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

Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling.

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

Proceedings of the Forty-first International Conference on Machine Learning, 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