Publications 2021
 

Journals

Niederschlags-Abfluss-Modellierung mit Long Short-Term Memory (LSTM)

Rainfall–runoff prediction at multiple timescales with a single Long Short-Term Memory network

A note on leveraging synergy in multiple meteorological datasets with deep learning for rainfall-runoff modeling

The Promise of AI for DILI Prediction

Author(s): Andreu Vall, Yogesh Sabnis, Jiye Shi, Reiner Class, Sepp Hochreiter, Günter Klambauer
Published: Frontiers in Artificial Intelligence, April, 2021. doi: 10.3389/frai.2021.638410

Conferences

Learning 3D Granular Flow Simulations

Benchmarking recent Deep Learning methods on the extended Tox21 data set

Author(s): Philipp Seidl, Christina Halmich, Andreas Mayr, Andreu Vall, Peter Ruch, Sepp Hochreiter, Günter Klambauer
Published: 19th International Workshop on (Q)SAR in Environmental and Health Sciences (QSAR2021), Poster Session, June 2021, online

Comparative assessment of interpretability methods of deep activity models for hERG

Author(s): Johannes Schimunek, Lukas Friedrich, Daniel Kuhn, Sepp Hochreiter, Friedrich Rippmann, Günter Klambauer
Published: 19th International Workshop on (Q)SAR in Environmental and Health Sciences (QSAR2021), Poster Session, June 2021, online

Large-scale river network modeling using Graph Neural Networks

Author(s): Daniel Klotz, Martin Gauch, Christoph Klingler, Grey Nearing, Sepp Hochreiter
Published: Video/Presentation at EGU General Assembly 2021, April 2021 (online)

Multi-Timescale LSTM for Rainfall–Runoff Forecasting

Author(s): Frederik Kratzert, Grey Nearing, Jimmy Lin, Sepp Hochreiter, Johannes Brandstetter, Daniel Klotz
Published: Video/Presentation at EGU General Assembly 2021, April 2021 (online)

Uncertainty estimation with LSTM based rainfall-runoff models

Author(s): Frederik Kratzert, Martin Gauch, Alden K. Sampson, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter, Grey Nearing
Published: Video/Presentation at EGU General Assembly 2021, April 2021 (online)

LamaH: Large-sample Data for Hydrology in Central Europe

Author(s): Christoph Klingler, Mathew Herrnegger, Frederik Kratzert, Karsten Schulz
Published: Video/Presentation at EGU General Assembly 2021, April 2021 (online)

Publications (non-peer-reviewed)

Machine Learning based COVID-19 Diagnosis from Blood Tests with Robustness to Domain ShiftsmedRxiv

Modern Hopfield Networks for Few- and Zero-Shot Reaction PredictionarXiv.org

Author(s): Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer
Published:

arXiv:2104.03279, 2021 https://arxiv.org/abs/2104.03279

MC-LSTM: Mass-Conserving LSTMarXiv.org

Author(s): Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer
Published:

arXiv:2101.05186, 2021 https://arxiv.org/abs/2101.05186v2

Trusted Artificial Intelligence: Towards Certification of Machine Learning ApplicationsarXiv.org

Author(s): Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler
Published:

arXiv:2103.16910, 2021 https://arxiv.org/abs/2103.16910v1

immuneML: an Ecosystem for Machine Learning Analysis of Adaptive Immune Receptor RepertoiresbioRxiv.org

Author(s): Milena Pavlović, Lonneke Scheffer,Keshav Motwani, Chakravarthi Kanduri, Radmila Kompova, Nikolay Vazov, Knut Waagan, Fabian L. M. Bernal, Alexandre Almeida Costa, Brian Corrie, Rahmad Akbar, Ghadi S. Al Hajj, Gabriel Balaban, Todd M. Brusko, Maria Chernigovskaya, Scott Christley, Lindsay G. Cowell, Robert Frank, Ivar Grytten, Sveinung Gundersen, Ingrid Hobæk Haff, Sepp Hochreiter, Eivind Hovig, Ping-Han Hsieh, Günter Klambauer, Marieke L. Kuijjer, Christin Lund-Andersen, Antonio Martini, Thomas Minotto, Johan Pensar, Knut Rand, Enrico Riccardi, Philippe A. Robert, Artur Rocha, Andrei Slabodkin, Igor Snapkov, Ludvig M. Sollid, Dmytro Titov, Cédric R. Weber, Michael Widrich, Gur Yaari, Victor Greiff, Geir Kjetil Sandve
Published:

bioRxiv, 2021 DOI: 10.1101/2021.03.08.433891