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Publikationen 2019

Zeitschriften

Towards learning universal, regional, and local hydrologicalbehaviors via machine learning applied tolarge-sample datasets Toward Improved Predictions in Ungauged Basins: Exploiting the Power of Machine Learning
Machine Learning in Drug Discovery
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
 

Konferenzen

On the Convergence of Episodic Reinforcement Learning Algorithms at the Example of RUDDER
Author(s): Markus Holzleitner, Jose A. Arjona-Medina, Marius-Constantin Dinu, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

A Two Time-Scale Update Rule Ensuring Convergence of Episodic Reinforcement Learning Algorithms at the Example of RUDDER
Author(s): Markus Holzleitner, Jose A. Arjona-Medina, Marius-Constantin Dinu, Andreu Vall, Lukas Gruber, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

Industry-scale Application and Evaluation of Deep Learning for Drug Target Prediction
Author(s): Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir Chupakhin, Hugo Ceulemans, Joerg Wegner, Jose-Felipe Golib-Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa,  Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

A GAN based solver idea for derivative-free optimization problems
Author(s): Hubert Ramsauer, Johannes Brandstetter, Michael Gillhofer, Bernhard Schäfl, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

A GAN based solver of black-box inverse problems
Author(s): Michael Gillhofer, Hubert Ramsauer, Johannes Brandstetter, Bernhard Schäfl, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

Uncertainty Estimation Methods to Support Decision-Making in Early Phases of Drug Discovery
Author(s): Philipp Renz, Thomas Adler, Sepp Hochreiter, Günter Klambauer
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

Patch Refinement: Localized 3D Object Detection LSTM-Designed Quantum Experiments
Author(s): Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

Using LSTMs for climate change assessment studies on droughts and floods
Author(s): Frederik Kratzert, Daniel Klotz, Johannes Brandstetter, Pieter-Jan Hoedt, Grey Nearing, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

RUDDER: Return Decomposition for Delayed Rewards
Author(s): José Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Johannes Brandstetter, Sepp Hochreiter
Published:

Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

Human-level Protein Localization with Convolutional Neural Networks ICLR
Author(s): Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl, Sepp Hochreiter, Günter Klambauer
Published: International Conference on Learning Representations (ICLR 2019), May 6-9, 2019, New Orleans, US
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images
Author(s): Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher, Philipp Tschandl, Harald Kittler, Sepp Hochreiter, Wolfram Hötzenecker, Günter Klambauer
Published:

Machine Learning for Health Workshop, Conference Neural Information Processing Systems Foundation (NeurIPS 2019), December 8-14, 2019, Vancouver, Canada

https://arxiv.org/abs/1911.06616, öffnet eine externe URL in einem neuen Fenster

Towards the quantification of uncertainty for deep learning based rainfall-runoff models EGU
Author(s): Daniel Klotz, Frederik Kratzert, Mathew Herrnegger, Sepp Hochreiter, and Günter Klambauer
Published: Poster at EGU General Assembly 2019, April 7-12, 2019, Vienna, Austria
Using large data sets towards generating a catchment aware hydrological model for global applications EGU
Author(s): Frederik Kratzert, Daniel Klotz, Mathew Herrnegger, Sepp Hochreiter, and Günter Klambauer
Published: Poster at EGU General Assembly 2019, April 7-12, 2019, Vienna, Austria

Bücher/Buch Kapitel

Explaining and Interpreting LSTMs Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Author(s): Leila Arras, José Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
Editor(s): Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller
Published: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019, Part III, pp. 211-238, doi: 10.1007/978-3-030-28954-6, öffnet eine externe URL in einem neuen Fenster
Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Author(s): Markus Hofmarcher, Thomas Unterthiner, José Arjona-Medina, Günter Klambauer, Sepp Hochreiter, Bernhard Nessler
Editor(s): Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller
Published: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019, Part V, pp. 285-296, doi: 10.1007/978-3-030-28954-6, öffnet eine externe URL in einem neuen Fenster
Interpretable Deep Learning in Drug Discovery Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Author(s): Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner
Editor(s): Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Müller
Published: Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 2019, Part V, pp. 331-345, doi: 10.1007/978-3-030-28954-6, öffnet eine externe URL in einem neuen Fenster
NeuralHydrology – Interpreting LSTMs in Hydrology Explainable AI: Interpreting, Explaining and Visualizing Deep Learning