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- Science Park 3 - Floor 3 - Room 327
- +43 732 2468 4528
- +43 732 2468 4539
- mayr(at)ml.jku.at
Personal data/education
- MSc in Computer Science and Bioinformatics from Johannes Kepler University Linz, Austria
- PhD of Natural Sciences in Computer Science, Johannes Kepler University Linz, Austria
Research topics
- Deep Neural Networks
- Theoretical Properties of DNNs
- Cheminformatics
- Deep Learning for Physics
- Graph Networks
Selected Publications
- Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter: Boundary Graph Neural Networks for 3D Simulations, 2023 https://arxiv.org/abs/2106.11299, opens an external URL in a new window
accepted for an oral talk in the technical program at the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)
Official Proceedings not yet available
Code: https://github.com/ml-jku/bgnn, opens an external URL in a new window
Data: https://ml.jku.at/research/bgnn/download/, opens an external URL in a new window - Andreas Mayr, Sebastian Lehner, Arno Mayrhofer, Christoph Kloss, Sepp Hochreiter, Johannes Brandstetter: Learning 3D Granular Flow Simulations, 2021 https://arxiv.org/abs/2105.01636, opens an external URL in a new window
accepted at Deep Learning for Simulation (SimDL) Workshop @ ICLR 2021 (https://simdl.github.io/schedule/, opens an external URL in a new window)
Poster: https://simdl.github.io/posters/42-supp_poster.pdf, opens an external URL in a new window
Contributed Talk: https://slideslive.de/38955315/learning-3d-granular-flow-simulations?ref=speaker-10792-latest, opens an external URL in a new window - 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: Industry-scale application and evaluation of deep learning for drug target prediction, Journal of Cheminformatics, 2020 https://doi.org/10.1186/s13321-020-00428-5, opens an external URL in a new window
- Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter: Cross-Domain Few-Shot Learing by Representation Fusion, 2020 https://arxiv.org/abs/2010.06498, opens an external URL in a new window
- Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Marvin Steijaert, Jörg K. Wegner, Hugo Ceulemans, Djork-Arne Clevert, Sepp Hochreiter: Large-scale comparison of machine learning methods for drug target prediction on ChEMBL, opens an external URL in a new window, Chemical Science, 2018
- Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter: Self-Normalizing Neural Networks, opens an external URL in a new window, Advances in Neural Information Processing Systems 30 (NIPS), 2017
- Michael Treml, José Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Bernhard Nessler, Sepp Hochreiter Speeding up Semantic Segmentation for Autonomous Driving, opens an external URL in a new window, Machine Learning for Intelligent Transportation Systems, in conjunction with Neural Information Processing Systems (NIPS), 2016
- Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter: Deep Learning for Drug Target Prediction, GPU Technology Conference Europe (GTC Europe), 2016,
Best Poster Award - Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter: DeepTox: Toxicity Prediction using Deep Learning, opens an external URL in a new window Frontiers in Environmental Science, 2016
- Federica Eduati, Lara M Mangravite, Tao Wang, Hao Tang, ... , Sepp Hochreiter, Günter Klambauer, Andreas Mayr, ... , Ivan Rusyn, Fred A Wright, Gustavo Stolovitzky, Yang Xie, Julio Saez-Rodriguez: Prediction of human population responses to toxic compounds by a collaborative competition, opens an external URL in a new window Nature Biotechnology, Advance online publication, 2015
- Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter: Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map, opens an external URL in a new window Bioinformatics, 2015
- Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter: Toxicity Prediction using Deep Learning, opens an external URL in a new window, arXiv pre-print, 2015
- Djork-Arne Clevert, Thomas Unterthiner, Andreas Mayr, Hubert Ramsauer, Sepp Hochreiter:Rectified Factor Networks, opens an external URL in a new window arXiv pre-print, 2015
- Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Marvin Steijaert, Jörg Wegner, Hugo Ceulemans, Sepp Hochreiter: Deep Learning as an Opportunity in Virtual Screening, opens an external URL in a new window,Deep Learning and Representation Learning Workshop, in conjunction with Neural Information Processing Systems (NIPS 2014), Montreal, Canada, 2014
- Marc Streit, Samuel Gratzl, Michael Gillhofer, Andreas Mayr, Andreas Mitterecker, Sepp Hochreiter: Furby: fuzzy force-directed bicluster visualization, opens an external URL in a new window BMC Bioinformatics, 2014
- Djork-Arne Clevert, Andreas Mayr, Andreas Mitterecker, Günter Klambauer, Armand Valsesia, Karl Forner, Marianne Tuefferd, Willem Talloen, Jerome Wojcik, Hinrich Göhlmann, Sepp Hochreiter Increasing the discovery power of -omics studies, opens an external URL in a new window Systems Biomedicine, 2013
- Günter Klambauer, Karin Schwarzbauer, Andreas Mayr, Djork-Arne Clevert, Andreas Mitterecker, Ulrich Bodenhofer, Sepp Hochreiter cn.MOPS: mixture of Poissons for discovering copy number variations in next generation sequencing data with a low false discovery rate, opens an external URL in a new window, Nucl. Acids Res., 2012
- Djork-Arne Clevert, Andreas Mitterecker, Andreas Mayr, Günter Klambauer, Marianne Tuefferd, An De Bondt, Willem Talloen, Hinrich Göhlmann, Sepp Hochreiter: cn.FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate, opens an external URL in a new window, Nucl. Acids Res., 2011
- Sepp Hochreiter, Ulrich Bodenhofer, Martin Heusel, Andreas Mayr, Andreas Mitterecker, Adetayo Kasim, Tatsiana Khamiakova, Suzy Van Sanden, Dan Lin, Willem Talloen, Luc Bijnens, Hinrich H.W. Göhlmann, Ziv Shkedy, Djork-Arne Clevert: FABIA: Factor Analysis for Bicluster Acquisition, opens an external URL in a new window, Bioinformatics, 2010
Teaching
- Exercises in Theoretical Concepts of Machine Learning
- Exercises in Machine Learning: Unsupervised Techniques
- Exercises in Bioinformatics (for students of Biological Chemistry)
- Exercises Bioinformatics II: Theoretical Bioinformatics and Machine Learning
