G. Klambauer

Most-cited papers

Self-Normalizing Neural Networks
G. Klambauer, T. Unterthiner, Andreas Mayr, S. Hochreiter
2017Neural Information Processing Systems2,955 citations
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Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets
Frederik Kratzert, D. Klotz, Guy Shalev, G. Klambauer +2 more
2019Hydrology and Earth System Sciences1,019 citations Open access
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DeepTox: Toxicity Prediction using Deep Learning
Andreas Mayr, G. Klambauer, T. Unterthiner, S. Hochreiter
2016Frontiers in Environmental Science978 citations Open access
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Hopfield Networks is All You Need
H. Ramsauer, Bernhard Schafl, Johannes Lehner, Philipp Seidl +11 more
2020International Conference on Learning Representations788 citations
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xLSTM: Extended Long Short-Term Memory
Maximilian Beck, Korbinian Pöppel, M. Spanring, Andreas Auer +5 more
2024Neural Information Processing Systems720 citations
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DeepSynergy: predicting anti-cancer drug synergy with Deep Learning
Kristina Preuer, Richard P. I. Lewis, S. Hochreiter, A. Bender +2 more
2017Bioinform.620 citations Open access
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GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, Bernhard Nessler +2 more
2017arXiv.org519 citations
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
M. Menden, Dennis Wang, M. Mason, B. Szalai +350 more
2019Nature Communications321 citations Open access
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Graph networks for molecular design
Rocío Mercado, T. Rastemo, Edvard Lindelöf, G. Klambauer +3 more
2020Machine Learning: Science and Technology207 citations Open access
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Repurposing high-throughput image assays enables biological activity prediction for drug discovery
J. Simm, G. Klambauer, A. Arany, M. Steijaert +14 more
2018Cell Chemical Biology205 citations Open access
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Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling
D. Klotz, Frederik Kratzert, M. Gauch, Alden Keefe Sampson +4 more
2020Hydrology and Earth System Sciences195 citations Open access
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Toxicity Prediction using Deep Learning
T. Unterthiner, Andreas Mayr, G. Klambauer, S. Hochreiter
2015arXiv.org166 citations
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On failure modes in molecule generation and optimization.
Philipp Renz, Dries Van Rompaey, J. Wegner, S. Hochreiter +1 more
2019Drug Discovery Today : Technologies145 citations Open access
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TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
Andreas Auer, Patrick Podest, Daniel Klotz, Sebastian Bock +2 more
2025Neural Information Processing Systems144 citations
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CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
Andreas Fürst, Elisabeth Rumetshofer, Viet-Hung Tran, H. Ramsauer +7 more
2021Neural Information Processing Systems133 citations Open access
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Prediction of human population responses to toxic compounds by a collaborative competition
F. Eduati, L. Mangravite, Tao Wang, Hao Tang +120 more
2015Nature Biotechnology112 citations Open access
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NeuralHydrology - Interpreting LSTMs in Hydrology
Frederik Kratzert, M. Herrnegger, D. Klotz, S. Hochreiter +1 more
2019Explainable AI109 citations Open access
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xLSTM: Extended Long Short-Term Memory
Andreas Auer, Maximilian Beck, J. Brandstetter, S. Hochreiter +5 more
2024Advances in Neural Information Processing Systems 37106 citations Open access
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Interpretable Deep Learning in Drug Discovery
Kristina Preuer, G. Klambauer, F. Rippmann, S. Hochreiter +1 more
2019Explainable AI105 citations Open access
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Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks
Philipp Seidl, Philipp Renz, N. Dyubankova, Paulo Neves +5 more
2022Journal of Chemical Information and Modeling97 citations Open access
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Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project.
Bie M. P. Verbist, G. Klambauer, L. Vervoort, W. Talloen +5 more
2015Drug Discovery Today94 citations Open access
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MC-LSTM: Mass-Conserving LSTM
Pieter-Jan Hoedt, Frederik Kratzert, D. Klotz, C. Halmich +4 more
2021International Conference on Machine Learning93 citations
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Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling
Frederik Kratzert, D. Klotz, Guy Shalev, G. Klambauer +2 more
2019arXiv.org92 citations Open access
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panelcn.MOPS: Copy‐number detection in targeted NGS panel data for clinical diagnostics
G. Povysil, A. Tzika, Julia Vogt, Verena Haunschmid +5 more
2017Human Mutation84 citations Open access
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The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires
Milena Pavlović, L. Scheffer, K. Motwani, C. Kanduri +38 more
2021Nature Machine Intelligence82 citations Open access
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Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields
T. Unterthiner, Bernhard Nessler, Calvin Seward, G. Klambauer +3 more
2017International Conference on Learning Representations82 citations
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Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language
Philipp Seidl, Andreu Vall, S. Hochreiter, G. Klambauer
2023International Conference on Machine Learning81 citations Open access
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Industry-scale application and evaluation of deep learning for drug target prediction
Noé Sturm, Andreas Mayr, Thanh Le Van, V. Chupakhin +15 more
2020Journal of Cheminformatics53 citations Open access
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Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction
Philippe A. Robert, R. Akbar, R. Frank, Milena Pavlović +21 more
2022Nature Computational Science52 citations Open access
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Cross-Domain Few-Shot Learning by Representation Fusion
Thomas Adler, J. Brandstetter, M. Widrich, Andreas Mayr +4 more
2020arXiv.org50 citations
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Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks
M. Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch +7 more
2020Social Science Research Network49 citations Open access
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Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation
M. Hofmarcher, T. Unterthiner, J. Arjona-Medina, G. Klambauer +2 more
2019Explainable AI47 citations
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Context-enriched molecule representations improve few-shot drug discovery
Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn +3 more
2023International Conference on Learning Representations42 citations Open access
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The Promise of AI for DILI Prediction
Andreu Vall, Y. Sabnis, Jiye Shi, R. Class +2 more
2021Frontiers in Artificial Intelligence41 citations Open access
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Quantification of Uncertainty with Adversarial Models
Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, G. Klambauer +1 more
2023Neural Information Processing Systems38 citations Open access
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DEXUS: identifying differential expression in RNA-Seq studies with unknown conditions
G. Klambauer, T. Unterthiner, S. Hochreiter
2013Nucleic Acids Research32 citations Open access
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VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
Florian Sestak, Lisa Schneckenreiter, J. Brandstetter, S. Hochreiter +2 more
2024arXiv.org30 citations
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Practical notes on building molecular graph generative models
Rocío Mercado, T. Rastemo, Edvard Lindelöf, G. Klambauer +3 more
2020Applied AI Letters30 citations Open access
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Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictions
Emese Sükei, Elisabeth Rumetshofer, N. Schmidinger, Andreas Mayr +3 more
2024Scientific Reports29 citations Open access
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Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
N. Schmidinger, Lisa Schneckenreiter, Philipp Seidl, Johannes Schimunek +6 more
2024International Conference on Learning Representations26 citations
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Artificial Intelligence Meets Toxicology.
I. Tetko, G. Klambauer, Djork-Arné Clevert, Imran Shah +1 more
2022Chemical Research in Toxicology24 citations Open access
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Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map
G. Klambauer, Martin Wischenbart, M. Mahr, T. Unterthiner +2 more
2015Bioinform.24 citations Open access
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Identification of a type 1 diabetes–associated T cell receptor repertoire signature from the human peripheral blood
P. Rawat, M. Shapiro, L. Peters, M. Widrich +24 more
2026Science Advances19 citations
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xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
Maximilian Beck, Korbinian Pöppel, Phillip Lippe, Richard Kurle +4 more
2025International Conference on Machine Learning19 citations
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A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
Thomas Schmied, Thomas Adler, Vihang Patil, Maximilian Beck +5 more
2024International Conference on Machine Learning19 citations
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Principled Weight Initialisation for Input-Convex Neural Networks
Pieter-Jan Hoedt, G. Klambauer
2023Neural Information Processing Systems19 citations
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Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction
Philipp Seidl, Philipp Renz, N. Dyubankova, Paulo Neves +5 more
202119 citations
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Multi-Task Deep Networks for Drug Target Prediction
T. Unterthiner, Andreas Mayr, G. Klambauer, M. Steijaert +2 more
201519 citations
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Human-level Protein Localization with Convolutional Neural Networks
Elisabeth Rumetshofer, M. Hofmarcher, Clemens Röhrl, S. Hochreiter +1 more
2018International Conference on Learning Representations16 citations
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TiRex-2: Generalizing TiRex to Multivariate Data and Streaming
Patrick Podest, Marco Pichler, Elias Bürger, Levente Zólyomi +6 more
2026arXiv.org15 citations
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