Uncertainty Estimation
2023
K. Schweighofer, L. Aichberger, M. Ielanskyi, G. Klambauer, and S. Hochreiter (2023) Quantification of Uncertainty with Adversarial Models. arXiv:2307.03217, 2023-07-06. (more) (download)
A. Auer, M. Gauch, D. Klotz, and S. Hochreiter (2023) Conformal Prediction for Time Series with Modern Hopfield Networks. arXiv:2303.12783, 2023-03-22. (more) (download)
D. Klotz, M. Gauch, G. Nearing, S. Hochreiter, and F. Kratzert (2023) The Persistence of Errors: How Evaluating Models over Data Partitions Relates to a Global Evaluation. EGU23-15221, 2023-02-22. (more) (download)
2022
D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, J. Brandstetter, G. Klambauer, S. Hochreiter, and G. Nearing (2022) Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. Hydrology and Earth System Sciences, 26, 6, 1673-1693, 2022-03-31. (more) (download)
2021
D. Klotz, F. Kratzert, M. Gauch, A. K. Sampson, G. Klambauer, J. Brandstetter, S. Hochreiter, and G. Nearing (2021) Uncertainty Estimation with LSTM Based Rainfall-Runoff Models. EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13308, 2021-03-03. (more) (download)