NeuralHydrology - Interpreting LSTMs in Hydrology. - Frederik Kratzert; Mathew Herrnegger; Daniel Klotz; Sepp Hochreiter; Günter Klambauer (CoRR, 2019)

Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling. - Frederik Kratzert; Daniel Klotz; Guy Shalev; Günter Klambauer; Sepp Hochreiter; Grey Nearing (CoRR, 2019)

Using LSTMs for climate change assessment studies on droughts and floods. - Frederik Kratzert; Daniel Klotz; Johannes Brandstetter; Pieter-Jan Hoedt; Grey Nearing; Sepp Hochreiter (CoRR, 2019)

Accurate Hydrologic Modeling Using Less Information. - Guy Shalev; Ran El-Yaniv; Daniel Klotz; Frederik Kratzert; Asher Metzger; Sella Nevo (CoRR, 2019)

NeuralHydrology - Interpreting LSTMs in Hydrology. - Frederik Kratzert; Mathew Herrnegger; Daniel Klotz; Sepp Hochreiter; Günter Klambauer (Explainable AI, 2019)

Rainfall-Runoff Prediction at Multiple Timescales with a Single Long Short-Term Memory Network. - Martin Gauch; Frederik Kratzert; Daniel Klotz; Grey Nearing; Jimmy Lin; Sepp Hochreiter (CoRR, 2020)

Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. - Daniel Klotz; Frederik Kratzert; Martin Gauch; Alden Keefe Sampson; Günter Klambauer; Sepp Hochreiter; Grey Nearing (CoRR, 2020)

MC-LSTM: Mass-Conserving LSTM. - Pieter-Jan Hoedt; Frederik Kratzert; Daniel Klotz; Christina Halmich; Markus Holzleitner; Grey Nearing; Sepp Hochreiter; Günter Klambauer (ICML, 2021)

Few-Shot Learning by Dimensionality Reduction in Gradient Space. - Martin Gauch; Maximilian Beck; Thomas Adler; Dmytro Kotsur; Stefan Fiel; Hamid Eghbal-zadeh; Johannes Brandstetter; Johannes Kofler; Markus Holzleitner; Werner Zellinger; Daniel Klotz; Sepp Hochreiter; et al. (CoLLAs, 2022)

NeuralHydrology - A Python library for Deep Learning research in hydrology. - Frederik Kratzert; Martin Gauch; Grey Nearing; Daniel Klotz (J. Open Source Softw., 2022)

Conformal Prediction for Time Series with Modern Hopfield Networks. - Andreas Auer; Martin Gauch; Daniel Klotz; Sepp Hochreiter (NeurIPS, 2023)

Simplified priors for Object-Centric Learning. - Vihang Prakash Patil; Andreas Radler; Daniel Klotz; Sepp Hochreiter (CoLLAs, 2024)

Energy-based Hopfield Boosting for Out-of-Distribution Detection. - Claus Hofmann; Simon Schmid; Bernhard Lehner; Daniel Klotz; Sepp Hochreiter (NeurIPS, 2024)

TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning. - Andreas Auer; Patrick Podest; Daniel Klotz; Sebastian Böck; Günter Klambauer; Sepp Hochreiter (CoRR, 2025)