Publications
Lin, Y., Bathiany, S., Badri, M., Gelbrecht, M., Hess, P., Groenke, B., … & Boers, N. (2025). NeuralCrop: Combining physics and machine learning for improved crop yield predictions. arXiv preprint arXiv:2512.20177. [link]
Bochow, N., Hess, P., & Robinson, A. (2025). Physics-constrained generative machine learning-based high-resolution downscaling of Greenland’s surface mass balance and surface temperature. arXiv preprint arXiv:2507.22485. [link]
Hess, P., Gelbrecht, M., Schötz, C., Aich, M., Huang, Y., Yang, S., & Boers, N. (2025). Generating time-consistent dynamics with discriminator-guided image diffusion models. arXiv preprint arXiv:2505.09089. [link]
Aich, M., Bathiany, S., Hess, P., Huang, Y., & Boers, N. (2025). Diffusion models for probabilistic precipitation generation from atmospheric variables. arXiv preprint arXiv:2504.00307. [link]
Hess, P., Aich, M., Pan, B., & Boers, N. (2025). Fast, Scale-Adaptive, and Uncertainty-Aware Downscaling of Earth System Model Fields with Generative Foundation Models. Nature Machine Intelligence. [link]
Chen, M., Qian, Z., Boers, N., Creutzig, F., Camps-Valls, G., Hubacek, K., … & Lü, G. (2024). Collaboration between artificial intelligence and Earth science communities for mutual benefit. Nature Geoscience, 17(10), 949-952. [link]
Aich, M., Hess, P., Pan, B., Bathiany, S., Huang, Y., & Boers, N. (2024). Conditional diffusion models for downscaling & bias correction of Earth system model precipitation. arXiv preprint [link].
Hess, P., Lange, S., Schötz, C., & Boers, N. (2023). Deep Learning for Bias‐Correcting CMIP6‐Class Earth System Models. Earth’s Future, 11(10), e2023EF004002. [link]
Hess, P., Drüke, M., Petri, S., Strnad, F. M., & Boers, N. (2022). Physically constrained generative adversarial networks for improving precipitation fields from Earth system models. Nature Machine Intelligence, 4(10), 828-839. [link]
Hess, P., & Boers, N. (2022). Deep learning for improving numerical weather prediction of heavy rainfall. Journal of Advances in Modeling Earth Systems, 14(3), e2021MS002765. [link]