Peter D. Düben

Orcid: 0000-0002-4610-3326

According to our database1, Peter D. Düben authored at least 28 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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On csauthors.net:

Bibliography

2024
Neural general circulation models for weather and climate.
Nat., August, 2024

Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization.
J. Mach. Learn. Res., 2024

DiffDA: a Diffusion model for weather-scale Data Assimilation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Neural General Circulation Models.
CoRR, 2023

WeatherBench 2: A benchmark for the next generation of data-driven global weather models.
CoRR, 2023

2022
ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast.
CoRR, 2022

A Generative Deep Learning Approach to Stochastic Downscaling of Precipitation Forecasts.
CoRR, 2022

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

An open science exploration of global 1-km simulations of the earth's atmosphere.
Proceedings of the 18th IEEE International Conference on e-Science, 2022

2021
Compressing atmospheric data into its real information content.
Nat. Comput. Sci., 2021

The digital revolution of Earth-system science.
Nat. Comput. Sci., 2021

TRU-NET: a deep learning approach to high resolution prediction of rainfall.
Mach. Learn., 2021

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction.
Int. J. High Perform. Comput. Appl., 2021

Machine Learning Emulation of Urban Land Surface Processes.
CoRR, 2021

Probabilistic Forecasting with Conditional Generative Networks via Scoring Rule Minimization.
CoRR, 2021

Mixed-precision for Linear Solvers in Global Geophysical Flows.
CoRR, 2021

Machine Learning Emulation of 3D Cloud Radiative Effects.
CoRR, 2021

2020
Machine-Learned Preconditioners for Linear Solvers in Geophysical Fluid Flows.
CoRR, 2020

Deep Learning for Post-Processing Ensemble Weather Forecasts.
CoRR, 2020

2019
Predicting Weather Uncertainty with Deep Convnets.
CoRR, 2019

Accelerating High-Resolution Weather Models with Deep-Learning Hardware.
Proceedings of the Platform for Advanced Scientific Computing Conference, 2019

2017
Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures.
Comput. Phys. Commun., 2017

Validating optimisations for chaotic simulations.
Proceedings of the 27th International Conference on Field Programmable Logic and Applications, 2017

2015
Lower precision for higher accuracy: Precision and resolution exploration for shallow water equations.
Proceedings of the 2015 International Conference on Field Programmable Technology, 2015

Architectures and Precision Analysis for Modelling Atmospheric Variables with Chaotic Behaviour.
Proceedings of the 23rd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2015

Opportunities for energy efficient computing: a study of inexact general purpose processors for high-performance and big-data applications.
Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition, 2015

2014
The use of imprecise processing to improve accuracy in weather & climate prediction.
J. Comput. Phys., 2014

2012
A discontinuous/continuous low order finite element shallow water model on the sphere.
J. Comput. Phys., 2012


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