Günter Klambauer
Johannes Kepler University of Linz(AT)Salzgitter Group (Singapore)(SG)
Publications by Year
Research Areas
Computational Drug Discovery Methods, Machine Learning in Materials Science, Hydrological Forecasting Using AI, Protein Structure and Dynamics, Hydrology and Watershed Management Studies
Most-Cited Works
- → DeepTox: Toxicity Prediction using Deep Learning(2016)1,008 cited
- → DeepSynergy: predicting anti-cancer drug synergy with Deep Learning(2017)651 cited
- → Large-scale comparison of machine learning methods for drug target prediction on ChEMBL(2018)589 cited
- → Self-Normalizing Neural Networks(2017)515 cited
- → cn.MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate(2012)470 cited
- GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium(2017)
- → Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery(2018)326 cited
- → Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery(2018)248 cited
- → Uncertainty estimation with deep learning for rainfall–runoff modeling(2022)205 cited
- → On failure modes in molecule generation and optimization(2019)164 cited