Go to JKU Homepage
Institute for Machine Learning
What's that?

Institutes, schools, other departments, and programs create their own web content and menus.

To help you better navigate the site, see here where you are at the moment.

Publications 2019

Journals

Towards learning universal, regional, and local hydrologicalbehaviors via machine learning applied tolarge-sample data 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

Conferences

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
Author(s): Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter
Published:

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

https://arxiv.org/abs/1910.04093, opens an external URL in a new window

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

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 Klambaue
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, opens an external URL in a new window

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
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

Books/Book Chapters

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, opens an external URL in a new window
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, opens an external URL in a new window
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, opens an external URL in a new window
NeuralHydrology – Interpreting LSTMs in Hydrology Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
Author(s): Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer
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. 347-362, doi: 10.1007/978-3-030-28954-6, opens an external URL in a new window