Daniel Klotz

According to our database, Daniel Klotz authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

Energy-based Hopfield Boosting for Out-of-Distribution Detection.

Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Simplified priors for Object-Centric Learning.

Vihang Prakash Patil, Andreas Radler, Daniel Klotz, Sepp Hochreiter

Proceedings of the Conference on Lifelong Learning Agents, 2024

2023

Conformal Prediction for Time Series with Modern Hopfield Networks.

Andreas Auer, Martin Gauch, Daniel Klotz, Sepp Hochreiter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

NeuralHydrology - A Python library for Deep Learning research in hydrology.

Frederik Kratzert, Martin Gauch, Grey Nearing, Daniel Klotz

J. Open Source Softw., 2022

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, Sebastian Lehner

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

MC-LSTM: Mass-Conserving LSTM.

Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer

Proceedings of the 38th International Conference on Machine Learning, 2021

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

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

2019

NeuralHydrology - Interpreting LSTMs in Hydrology.

Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer

Proceedings of the Explainable AI: Interpreting, 2019

Accurate Hydrologic Modeling Using Less Information.

Guy Shalev, Ran El-Yaniv, Daniel Klotz, Frederik Kratzert, Asher Metzger, Sella Nevo

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

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

NeuralHydrology - Interpreting LSTMs in Hydrology.

Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer

CoRR, 2019