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2020 – today
- 2024
[j9]Lorenzo Pacchiardi, Rilwan A. Adewoyin, Peter Dueben, Ritabrata Dutta:
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization. J. Mach. Learn. Res. 25: 45:1-45:64 (2024)- [j8]Dmitrii Kochkov
, Janni Yuval, Ian Langmore, Peter C. Norgaard, Jamie A. Smith, Griffin Mooers, Milan Klöwer, James Lottes, Stephan Rasp, Peter D. Düben, Sam Hatfield, Peter W. Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, Stephan Hoyer:
Neural general circulation models for weather and climate. Nat. 632(8027): 1060-1066 (2024) - [c8]Langwen Huang, Lukas Gianinazzi, Yuejiang Yu, Peter D. Düben, Torsten Hoefler:
DiffDA: a Diffusion model for weather-scale Data Assimilation. ICML 2024 - [i13]Langwen Huang, Lukas Gianinazzi, Yuejiang Yu, Peter D. Düben, Torsten Hoefler:
DiffDA: a diffusion model for weather-scale data assimilation. CoRR abs/2401.05932 (2024) - 2023
- [i12]Stephan Rasp, 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, Peter Dueben, Carla Bromberg, Jared Sisk, Luke Barrington, Aaron Bell, Fei Sha:
WeatherBench 2: A benchmark for the next generation of data-driven global weather models. CoRR abs/2308.15560 (2023) - [i11]Dmitrii Kochkov, Janni Yuval, Ian Langmore, Peter C. Norgaard, Jamie A. Smith, Griffin Mooers, James Lottes, Stephan Rasp, Peter D. Düben, Milan Klöwer, Sam Hatfield, Peter W. Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, Stephan Hoyer:
Neural General Circulation Models. CoRR abs/2311.07222 (2023) - 2022
- [c7]Valentine Anantharaj, Samuel Hatfield, Inna Polichtchouk, Nils Wedi, Morgan E. O'Neill, Thomas Papatheodore, Peter Dueben:
An open science exploration of global 1-km simulations of the earth's atmosphere. e-Science 2022: 427-428 - [c6]Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler:
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts. NeurIPS 2022 - [i10]Lucy Harris, Andrew T. T. McRae, Matthew Chantry, Peter D. Düben, Tim N. Palmer:
A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts. CoRR abs/2204.02028 (2022) - [i9]Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler:
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast. CoRR abs/2206.14786 (2022) - 2021
- [j7]Tommaso Benacchio, Luca Bonaventura, Mirco Altenbernd, Chris D. Cantwell, Peter D. Düben, Mike Gillard, Luc Giraud, Dominik Göddeke, Erwan Raffin, Keita Teranishi, Nils Wedi:
Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction. Int. J. High Perform. Comput. Appl. 35(4) (2021) - [j6]Rilwan A. Adewoyin, Peter Dueben, Peter Watson, Yulan He, Ritabrata Dutta:
TRU-NET: a deep learning approach to high resolution prediction of rainfall. Mach. Learn. 110(8): 2035-2062 (2021) - [j5]Peter Bauer, Peter D. Düben, Torsten Hoefler, Tiago Quintino, Thomas C. Schulthess, Nils P. Wedi:
The digital revolution of Earth-system science. Nat. Comput. Sci. 1(2): 104-113 (2021) - [j4]Milan Klöwer, Miha Razinger, Juan J. Dominguez, Peter D. Düben, Tim N. Palmer:
Compressing atmospheric data into its real information content. Nat. Comput. Sci. 1(11): 713-724 (2021) - [i8]David Meyer, Robin J. Hogan, Peter D. Düben, Shannon L. Mason:
Machine Learning Emulation of 3D Cloud Radiative Effects. CoRR abs/2103.11919 (2021) - [i7]Jan Ackmann, Peter D. Düben, Tim N. Palmer, Piotr K. Smolarkiewicz:
Mixed-precision for Linear Solvers in Global Geophysical Flows. CoRR abs/2103.16120 (2021) - [i6]Lorenzo Pacchiardi, Rilwan Adewoyin, Peter Dueben, Ritabrata Dutta:
Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization. CoRR abs/2112.08217 (2021) - [i5]David Meyer, Sue Grimmond, Peter Dueben, Robin J. Hogan, Maarten van Reeuwijk:
Machine Learning Emulation of Urban Land Surface Processes. CoRR abs/2112.11429 (2021) - 2020
- [i4]Peter Grönquist, Chengyuan Yao, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Shigang Li, Torsten Hoefler:
Deep Learning for Post-Processing Ensemble Weather Forecasts. CoRR abs/2005.08748 (2020) - [i3]Rilwan Adewoyin, Peter Dueben, Peter Watson, Yulan He, Ritabrata Dutta:
TRU-NET: A Deep Learning Approach to High Resolution Prediction of Rainfall. CoRR abs/2008.09090 (2020) - [i2]Jan Ackmann, Peter D. Düben, Tim N. Palmer, Piotr K. Smolarkiewicz:
Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows. CoRR abs/2010.02866 (2020)
2010 – 2019
- 2019
- [c5]Sam Hatfield, Matthew Chantry, Peter D. Düben, Tim N. Palmer:
Accelerating High-Resolution Weather Models with Deep-Learning Hardware. PASC 2019: 1:1-1:11 - [i1]Peter Grönquist, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Luca Lavarini, Shigang Li, Torsten Hoefler:
Predicting Weather Uncertainty with Deep Convnets. CoRR abs/1911.00630 (2019) - 2017
- [j3]Francis P. Russell, Peter D. Düben, Xinyu Niu, Wayne Luk, Tim N. Palmer:
Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures. Comput. Phys. Commun. 221: 160-173 (2017) - [c4]James Stanley Targett, Peter D. Düben, Wayne Luk:
Validating optimisations for chaotic simulations. FPL 2017: 1-4 - 2015
- [c3]Peter D. Düben, Jeremy Schlachter, Parishkrati, Sreelatha Yenugula, John Augustine, Christian C. Enz, Krishna V. Palem, Tim N. Palmer:
Opportunities for energy efficient computing: a study of inexact general purpose processors for high-performance and big-data applications. DATE 2015: 764-769 - [c2]Francis P. Russell, Peter D. Düben, Xinyu Niu, Wayne Luk, Tim N. Palmer:
Architectures and Precision Analysis for Modelling Atmospheric Variables with Chaotic Behaviour. FCCM 2015: 171-178 - [c1]James Stanley Targett, Xinyu Niu, Francis P. Russell, Wayne Luk, Stephen Jeffress, Peter D. Düben:
Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations. FPT 2015: 208-211 - 2014
- [j2]Peter D. Düben, Hugh McNamara, Tim N. Palmer:
The use of imprecise processing to improve accuracy in weather & climate prediction. J. Comput. Phys. 271: 2-18 (2014) - 2012
- [j1]Peter D. Düben, Peter Korn, Vadym Aizinger:
A discontinuous/continuous low order finite element shallow water model on the sphere. J. Comput. Phys. 231(6): 2396-2413 (2012)
Coauthor Index
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last updated on 2024-12-10 20:52 CET by the dblp team
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