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Publikationen 2018

Zeitschriften


Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL  Chem. Sci Multivariate analytics of chromatographic data: Visual computing based on moving window factor models J. Chromatogr. B. Defining objective clusters for rabies virus sequences using affinity propagation clustering PLoS Neglect. Trop. Dis.

Konferenzen

End-to-End Learning of Pharmacological Assays from High-resolution Microscopy Images NIPS
Author(s):

Markus Hofmarcher, Elisabeth Rumetshofer, Markus Holzleitner, Bernhard Schäfl, Sepp Hochreiter, Günter Klambauer

Published: Women in Machine Learning Workshop, Conference Neural Information Processing Systems Foundation (NIPS 2018), December 3-8, 2018, Montreal, Canada
Interpretable Deep Learning in Drug Development NIPS
Author(s):

Kristina Preuer, Johannes Brandstetter, Günter Klambauer, Sepp Hochreiter, Thomas Unterthiner

Published: Women in Machine Learning Workshop, Conference Neural Information Processing Systems Foundation (NIPS 2018), December 3-8, 2018, Montreal, Canada
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery NIPS
Author(s):

Kristina Preuer, Philipp Renz, Thomas Unterthiner, Johannes Kofler, Sepp Hochreiter, Günter Klambauer

Published: Women in Machine Learning Workshop, Conference Neural Information Processing Systems Foundation (NIPS 2018), December 3-8, 2018, Montreal, Canada
Characterising Activation Functions By Their Backwards Dynamics Around Forward Fixed Points NIPS
 
Author(s):

Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer

Published: Conference Neural Information Processing Systems Foundation (NIPS 2018), December 3-8, 2018, Montreal, Canada  

 

GPU-driven Deep Learning Paves New Ways for Drug Discovery Through High-Content Imaging GTC
Author(s): Maciej Kandula, Elisabeth Rumetshofer, Markus Hofmarcher, Günter Klambauer, Sepp Hochreiter
Published: Poster at GPU Technology Conference 2018, October 9-11, 2018, Munich, Germany (Best Paper Award)
First Order Generative Adversarial Networks ICML
Author(s): Calvin Seward, Thomas Unterthiner, Urs Bergmann, Nikolay Jetchev, Sepp Hochreiter
Published: International Conference on Machine Learning, July 10-15, 2018, Stockholm, Sweden
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields ICLR
Author(s): Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter
Published: International Conference on Learning Representations, April 30 - May 03, 2018, Vancouver, Canada
Making Sense of Very Rare and Private Single-Nucleotide Variants MAQC
Author(s): Ulrich Bodenhofer, Sepp Hochreiter
Published: MAQC Society Second Annual Meeting, February 24-27, 2018, Shanghai, China

Publikationen (non-peer-reviewed)

First Order Generative Adversarial Networks arXiv.org RUDDER: Return Decomposition for Delayed Rewards arXiv.org
Title: RUDDER: Return Decomposition for Delayed Rewards  
Author(s): Jose A. Arjona-Medina, Michael Gillhofer, Michael Widrich, Thomas Unterthiner, Sepp Hochreiter
Published: arXiv.org, June 2018
Download: arXiv:1806.07857, öffnet eine externe URL in einem neuen Fenster
Video Demonstration:

https://www.youtube.com/playlist?list=PLDfrC-Vpg-CzVTqSjxVeLQZy3f7iv9vyY, öffnet eine externe URL in einem neuen Fenster

Source code: https://github.com/ml-jku/baselines-rudder, öffnet eine externe URL in einem neuen Fenster
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields arXiv.org

Abschlussarbeiten