A discontinuous/continuous low order finite element shallow water model on the sphere. - Peter D. Düben; Peter Korn; Vadym Aizinger (J. Comput. Phys., 2012)

The use of imprecise processing to improve accuracy in weather & climate prediction. - Peter D. Düben; Hugh McNamara; Tim N. Palmer (J. Comput. Phys., 2014)

Opportunities for energy efficient computing: a study of inexact general purpose processors for high-performance and big-data applications. - Peter D. Düben; Jeremy Schlachter; Parishkrati; Sreelatha Yenugula; John Augustine; Christian C. Enz; Krishna V. Palem; Tim N. Palmer (DATE, 2015)

Architectures and Precision Analysis for Modelling Atmospheric Variables with Chaotic Behaviour. - Francis P. Russell; Peter D. Düben; Xinyu Niu; Wayne Luk; Tim N. Palmer (FCCM, 2015)

Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations. - James Stanley Targett; Xinyu Niu; Francis P. Russell; Wayne Luk; Stephen Jeffress; Peter D. Düben (FPT, 2015)

Validating optimisations for chaotic simulations. - James Stanley Targett; Peter D. Düben; Wayne Luk (FPL, 2017)

Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures. - Francis P. Russell; Peter D. Düben; Xinyu Niu; Wayne Luk; Tim N. Palmer (Comput. Phys. Commun., 2017)

Accelerating High-Resolution Weather Models with Deep-Learning Hardware. - Sam Hatfield; Matthew Chantry; Peter D. Düben; Tim N. Palmer (PASC, 2019)

Predicting Weather Uncertainty with Deep Convnets. - Peter Grönquist; Tal Ben-Nun; Nikoli Dryden; Peter Dueben; Luca Lavarini; Shigang Li 002; Torsten Hoefler (CoRR, 2019)

Deep Learning for Post-Processing Ensemble Weather Forecasts. - Peter Grönquist; Chengyuan Yao; Tal Ben-Nun; Nikoli Dryden; Peter Dueben; Shigang Li 002; Torsten Hoefler (CoRR, 2020)

Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows. - Jan Ackmann; Peter D. Düben; Tim N. Palmer; Piotr K. Smolarkiewicz (CoRR, 2020)

Machine Learning Emulation of 3D Cloud Radiative Effects. - David Meyer; Robin J. Hogan; Peter D. Düben; Shannon L. Mason (CoRR, 2021)

Mixed-precision for Linear Solvers in Global Geophysical Flows. - Jan Ackmann; Peter D. Düben; Tim N. Palmer; Piotr K. Smolarkiewicz (CoRR, 2021)

Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan Adewoyin; Peter Dueben; Ritabrata Dutta (CoRR, 2021)

Machine Learning Emulation of Urban Land Surface Processes. - David Meyer; Sue Grimmond; Peter Dueben; Robin J. Hogan; Maarten van Reeuwijk (CoRR, 2021)

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. - Tommaso Benacchio; Luca Bonaventura; Mirco Altenbernd; Chris D. Cantwell; Peter D. Düben; Mike Gillard; Luc Giraud; Dominik Göddeke; Erwan Raffin; Keita Teranishi; Nils Wedi (Int. J. High Perform. Comput. Appl., 2021)

TRU-NET: a deep learning approach to high resolution prediction of rainfall. - Rilwan A. Adewoyin; Peter Dueben; Peter Watson; Yulan He 001; Ritabrata Dutta (Mach. Learn., 2021)

The digital revolution of Earth-system science. - Peter Bauer; Peter D. Düben; Torsten Hoefler; Tiago Quintino; Thomas C. Schulthess; Nils P. Wedi (Nat. Comput. Sci., 2021)

Compressing atmospheric data into its real information content. - Milan Klöwer; Miha Razinger; Juan J. Dominguez; Peter D. Düben; Tim N. Palmer (Nat. Comput. Sci., 2021)

An open science exploration of global 1-km simulations of the earth's atmosphere. - Valentine Anantharaj; Samuel Hatfield; Inna Polichtchouk; Nils Wedi; Morgan E. O'Neill; Thomas Papatheodore; Peter Dueben (e-Science, 2022)

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts. - Saleh Ashkboos; Langwen Huang; Nikoli Dryden; Tal Ben-Nun; Peter Dueben; Lukas Gianinazzi; Luca Kummer; Torsten Hoefler (NeurIPS, 2022)

A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts. - Lucy Harris; Andrew T. T. McRae; Matthew Chantry; Peter D. Düben; Tim N. Palmer (CoRR, 2022)

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast. - Saleh Ashkboos; Langwen Huang; Nikoli Dryden; Tal Ben-Nun; Peter Dueben; Lukas Gianinazzi; Luca Kummer; Torsten Hoefler (CoRR, 2022)

WeatherBench 2: A benchmark for the next generation of data-driven global weather models. - Stephan Rasp 001; Stephan Hoyer; Alexander Merose; Ian Langmore; Peter W. Battaglia; Tyler Russell; Alvaro Sanchez-Gonzalez; Vivian Yang; Rob Carver; Shreya Agrawal; Matthew Chantry; Zied Ben Bouallegue; et al. (CoRR, 2023)

Neural General Circulation Models. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; James Lottes; Stephan Rasp 001; Peter D. Düben; Milan Klöwer; Sam Hatfield; Peter W. Battaglia; et al. (CoRR, 2023)

DiffDA: a Diffusion model for weather-scale Data Assimilation. - Langwen Huang; Lukas Gianinazzi; Yuejiang Yu; Peter D. Düben; Torsten Hoefler (ICML, 2024)

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization. - Lorenzo Pacchiardi; Rilwan A. Adewoyin; Peter Dueben; Ritabrata Dutta (J. Mach. Learn. Res., 2024)

Neural general circulation models for weather and climate. - Dmitrii Kochkov; Janni Yuval; Ian Langmore; Peter C. Norgaard; Jamie A. Smith; Griffin Mooers; Milan Klöwer; James Lottes; Stephan Rasp 001; Peter D. Düben; Sam Hatfield; Peter W. Battaglia; et al. (Nat., 2024)