Stephan Rasp

According to our database, Stephan Rasp authored at least 11 papers between 2018 and 2024.

Collaborative distances:

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

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, Peter D. Düben, Sam Hatfield, Peter W. Battaglia, Alvaro Sanchez-Gonzalez, Matthew Willson, Michael P. Brenner, Stephan Hoyer

Nat., August, 2024

2023

Neural General Circulation Models.

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

CoRR, 2023

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

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

CoRR, 2023

2022

WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models.

Sagar Garg, Stephan Rasp, Nils Thuerey

CoRR, 2022

Increasing the accuracy and resolution of precipitation forecasts using deep generative models.

Ilan Price, Stephan Rasp

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Climate-Invariant Machine Learning.

Tom Beucler, Michael S. Pritchard, Janni Yuval, Ankitesh Gupta, Liran Peng, Stephan Rasp, Fiaz Ahmed, Paul A. O'Gorman, J. David Neelin, Nicholas J. Lutsko, Pierre Gentine

CoRR, 2021

2020

Towards Physically-Consistent, Data-Driven Models of Convection.

Tom Beucler, Michael S. Pritchard, Pierre Gentine, Stephan Rasp

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020

2019

Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling.

Tom Beucler, Stephan Rasp, Michael S. Pritchard, Pierre Gentine

CoRR, 2019

Combining crowd-sourcing and deep learning to understand meso-scale organization of shallow convection.

Stephan Rasp, Hauke Schulz, Sandrine Bony, Bjorn Stevens

CoRR, 2019

2018

Deep learning to represent sub-grid processes in climate models.

Stephan Rasp, Michael S. Pritchard, Pierre Gentine

CoRR, 2018

Neural networks for post-processing ensemble weather forecasts.

Stephan Rasp, Sebastian Lerch

CoRR, 2018