Andreas Mayr
Andreas Mayr
Institute for Machine Learning, Johannes Kepler University Linz
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Self-normalizing neural networks
G Klambauer, T Unterthiner, A Mayr, S Hochreiter
Advances in neural information processing systems 30, 2017
DeepTox: toxicity prediction using deep learning
A Mayr, G Klambauer, T Unterthiner, S Hochreiter
Frontiers in Environmental Science 3, 80, 2016
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL
A Mayr, G Klambauer, T Unterthiner, M Steijaert, JK Wegner, ...
Chemical science 9 (24), 5441-5451, 2018
cn. MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate
G Klambauer, K Schwarzbauer, A Mayr, DA Clevert, A Mitterecker, ...
Nucleic acids research 40 (9), e69-e69, 2012
FABIA: factor analysis for bicluster acquisition
S Hochreiter, U Bodenhofer, M Heusel, A Mayr, A Mitterecker, A Kasim, ...
Bioinformatics 26 (12), 1520-1527, 2010
Speeding up semantic segmentation for autonomous driving
M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...
Deep learning as an opportunity in virtual screening
T Unterthiner, A Mayr, G Klambauer, M Steijaert, JK Wegner, ...
Proceedings of the deep learning workshop at NIPS 27, 1-9, 2014
Toxicity prediction using deep learning
T Unterthiner, A Mayr, G Klambauer, S Hochreiter
arXiv preprint arXiv:1503.01445, 2015
Prediction of human population responses to toxic compounds by a collaborative competition
F Eduati, LM Mangravite, T Wang, H Tang, JC Bare, R Huang, T Norman, ...
Nature biotechnology 33 (9), 933-940, 2015
Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project
B Verbist, G Klambauer, L Vervoort, W Talloen, Z Shkedy, O Thas, ...
Drug discovery today 20 (5), 505-513, 2015
Furby: fuzzy force-directed bicluster visualization
M Streit, S Gratzl, M Gillhofer, A Mayr, A Mitterecker, S Hochreiter
BMC bioinformatics 15, 1-13, 2014
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
M Hofmarcher, A Mayr, E Rumetshofer, P Ruch, P Renz, J Schimunek, ...
arXiv preprint arXiv:2004.00979, 2020
Cross-Domain Few-Shot Learning by Representation Fusion
T Adler, J Brandstetter, M Widrich, A Mayr, D Kreil, M Kopp, G Klambauer, ...
arXiv preprint arXiv:2010.06498, 2020
Industry-scale application and evaluation of deep learning for drug target prediction
N Sturm, A Mayr, T Le Van, V Chupakhin, H Ceulemans, J Wegner, ...
Journal of Cheminformatics 12, 1-13, 2020
cn. FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate
DA Clevert, A Mitterecker, A Mayr, G Klambauer, M Tuefferd, AD Bondt, ...
Nucleic acids research 39 (12), e79-e79, 2011
Application of bioactivity profile-based fingerprints for building machine learning models
N Sturm, J Sun, Y Vandriessche, A Mayr, G Klambauer, L Carlsson, ...
Journal of chemical information and modeling 59 (3), 962-972, 2018
DeepTox: Toxicity prediction using deep learning
G Klambauer, T Unterthiner, A Mayr, S Hochreiter
Toxicol Lett 280, S69-S69, 2017
ELU-networks: fast and accurate CNN learning on imagenet
M Heusel, DA Clevert, G Klambauer, A Mayr, K Schwarzbauer, ...
NiN 8, 35.68, 2015
Boundary graph neural networks for 3d simulations
A Mayr, S Lehner, A Mayrhofer, C Kloss, S Hochreiter, J Brandstetter
Proceedings of the AAAI Conference on Artificial Intelligence 37 (8), 9099-9107, 2023
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map
G Klambauer, M Wischenbart, M Mahr, T Unterthiner, A Mayr, ...
Bioinformatics 31 (20), 3392-3394, 2015
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Artículos 1–20