Sebastian Schemm

According to our database, Sebastian Schemm authored at least 9 papers between 2022 and 2026.

Collaborative distances:

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

2026

Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts.

Fanny Lehmann, Firat Ozdemir, Yun Cheng, Torsten Hoefler, Sebastian Schemm, Benedikt Soja, Siddhartha Mishra

CoRR, May, 2026

Earth System Foundation Model (ESFM): A unified framework for heterogeneous data integration and forecasting.

Firat Ozdemir, Yun Cheng, Salman Mohebi, Fanny Lehmann, Simon Adamov, Zhenyi Zhang, Leonardo Trentini, Dana Grund, Oliver Fuhrer, Torsten Hoefler, Siddhartha Mishra, Sebastian Schemm, Benedikt Soja, Mathieu Salzmann

CoRR, May, 2026

Making Tunable Parameters State-Dependent in Weather and Climate Models with Reinforcement Learning.

Pritthijit Nath, Sebastian Schemm, Henry Moss, Peter Haynes, Emily Shuckburgh, Mark Webb

CoRR, January, 2026

2025

Error bounded compression for weather and climate applications.

Langwen Huang, Luigi Fusco, Florian Scheidl, Jan Zibell, Michael Armand Sprenger, Sebastian Schemm, Torsten Hoefler

CoRR, October, 2025

FedRAIN-Lite: Federated Reinforcement Algorithms for Improving Idealised Numerical Weather and Climate Models.

Pritthijit Nath, Sebastian Schemm, Henry Moss, Peter Haynes, Emily Shuckburgh, Mark Webb

CoRR, August, 2025

Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes.

Fanny Lehmann, Firat Ozdemir, Benedikt Soja, Torsten Hoefler, Siddhartha Mishra, Sebastian Schemm

CoRR, June, 2025

Building Machine Learning Limited Area Models: Kilometer-Scale Weather Forecasting in Realistic Settings.

Simon Adamov, Joel Oskarsson, Leif C. Denby, Tomas Landelius, Kasper Hintz, Simon Christiansen, Irene Schicker, Carlos Osuna, Fredrik Lindsten, Oliver Fuhrer, Sebastian Schemm

CoRR, April, 2025

2022

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks.

Kenza Amara, Rex Ying, Zitao Zhang, Zhihao Han, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang

CoRR, 2022

GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks.

Kenza Amara, Zhitao Ying, Zitao Zhang, Zhichao Han, Yang Zhao, Yinan Shan, Ulrik Brandes, Sebastian Schemm, Ce Zhang

Proceedings of the Learning on Graphs Conference, 2022