Martin Gauch

According to our database, Martin Gauch authored at least 10 papers between 2018 and 2023.

Collaborative distances:

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

2023

AI Increases Global Access to Reliable Flood Forecasts.

Grey Nearing, Deborah Cohen, Vusumuzi Dube, Martin Gauch, Oren Gilon, Shaun Harrigan, Avinatan Hassidim, Frederik Kratzert, Asher Metzger, Sella Nevo, Florian Pappenberger, Christel Prudhomme, Guy Shalev, Shlomo Shenzis, Tadele Tekalign, Dana Weitzner, Yossi Matias

CoRR, 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

The proper care and feeding of CAMELS: How limited training data affects streamflow prediction.

Martin Gauch, Juliane Mai, Jimmy Lin

Environ. Model. Softw., 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

A Data Scientist's Guide to Streamflow Prediction.

Martin Gauch, Jimmy Lin

CoRR, 2020

An Open-Source Interface to the Canadian Surface Prediction Archive.

Martin Gauch, James Bai, Juliane Mai, Jimmy Lin

Proceedings of the JCDL '20: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020, 2020

2018

Towards Simulation-Data Science - A Case Study on Material Failures.

Holger Trittenbach, Martin Gauch, Klemens Böhm, Katrin Schulz

Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018