Andreas Mayr

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Sepp HochreiterInstitute for Machine Learning, Johannes Kepler University LinzDirección de correo verificada de ml.jku.at
Günter KlambauerProf., LIT AI Lab & Institute for Machine Learning, Johannes Kepler UniversityDirección de correo verificada de ml.jku.at
Thomas UnterthinerGoogle DeepMindDirección de correo verificada de pm.me
Djork-Arné ClevertPfizer, VP, Machine Learning ResearchDirección de correo verificada de pfizer.com
Jörg Kurt WegnerDirector, In Silico Discovery, Janssen R&D, Cambridge, MA, USDirección de correo verificada de its.jnj.com
Hinrich WH GöhlmannDirector Discovery Data Science at GenmabDirección de correo verificada de genmab.com
Hugo CeulemansJanssenDirección de correo verificada de telenet.be
Ulrich BodenhoferProfessor for Artificial Intelligence, University of Applied Sciences Upper AustriaDirección de correo verificada de fh-hagenberg.at
Luc BijnensJanssen (J&J), University Hasselt, BelgiumDirección de correo verificada de UHasselt.be
Johannes BrandstetterJohannes Kepler University (JKU) LinzDirección de correo verificada de ml.jku.at
Hongming ChenAstrazeneca, Bioland Laboratory, Guangzhou LaboratoryDirección de correo verificada de grmh-gdl.cn
Ola EngkvistAstraZeneca R&D Gothenburg Orcid:0000-0003-4970-6461Dirección de correo verificada de astrazeneca.com
Andreas BenderUniversity of Cambridge; Pangea Bio; Universitatea Babeș-Bolyai; UMF ClujDirección de correo verificada de cam.ac.uk
Christoph KlossDirector, DCS ComputingDirección de correo verificada de dcs-computing.com
Marc StreitProfessor for Visual Data Science @ Johannes Kepler University LinzDirección de correo verificada de jku.at
Noé Sturm

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Andreas Mayr

Institute for Machine Learning, Johannes Kepler University Linz

Dirección de correo verificada de ml.jku.at - Página principal

Machine Learning Deep Learning Neural Networks Cheminformatics Bioinformatics


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Self-normalizing neural networks G Klambauer, T Unterthiner, A Mayr, S Hochreiter Advances in neural information processing systems 30, 2017	3462	2017
DeepTox: toxicity prediction using deep learning A Mayr, G Klambauer, T Unterthiner, S Hochreiter Frontiers in Environmental Science 3, 80, 2016	990	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	545	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	503	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	396	2010
Speeding up semantic segmentation for autonomous driving M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...	352	2016
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	248	2014
Toxicity prediction using deep learning T Unterthiner, A Mayr, G Klambauer, S Hochreiter arXiv preprint arXiv:1503.01445, 2015	127	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	121	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	110	2015
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	63	2020
Furby: fuzzy force-directed bicluster visualization M Streit, S Gratzl, M Gillhofer, A Mayr, A Mitterecker, S Hochreiter BMC bioinformatics 15, 1-13, 2014	62	2014
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	47	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	45	2020
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	36	2023
DeepTox: Toxicity prediction using deep learning G Klambauer, T Unterthiner, A Mayr, S Hochreiter Toxicol Lett 280, S69-S69, 2017	31	2017
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	29	2018
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	29	2011
ELU-networks: fast and accurate CNN learning on imagenet M Heusel, DA Clevert, G Klambauer, A Mayr, K Schwarzbauer, ... NiN 8, 35.68, 2015	28	2015
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	25	2015

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