Günter Klambauer

Johannes Kepler University of Linz — Austria

Computer Science · Physical Sciences

37h-index7.6kcitations132works8.62yr avg
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Research Topics

Computational Drug Discovery Methods(56), Machine Learning in Materials Science(37), Hydrological Forecasting Using AI(15), Protein Structure and Dynamics(14), Hydrology and Watershed Management Studies(14)

Publications127 total

VN-EGNN: E(3)- and SE(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
Journal of Cheminformatics·2025· 4 citedOpen Access
Domain shifts decrease the accuracy of machine learning algorithms to detect myocardial ischemia in ECG recordings: A multi-database analysis
2025Open Access
Machine Learning-Driven Optimization of Specific, Compact, and Efficient Base Editors via Single-Round Diversification
2025Open Access
Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data
arXiv (Cornell University)·2025Open Access
TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning
arXiv (Cornell University)·2025Open Access
MHNfs: Prompting In-Context Bioactivity Predictions for Low-Data Drug Discovery
Journal of Chemical Information and Modeling·2025· 1 citedOpen Access
Advancing OCT-Based Retinal Disease Classification with XLSTM: A Framework for Variable-Length Volume Processing
2025
LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities
arXiv (Cornell University)·2025Open Access
Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood
2024· 8 citedOpen Access
Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
arXiv (Cornell University)·2024· 5 citedOpen Access
Multi-modal representation learning in retinal imaging using self-supervised learning for enhanced clinical predictions
Scientific Reports·2024· 16 citedOpen Access
A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks
arXiv (Cornell University)·2024· 2 citedOpen Access
Diverse Hits in De Novo Molecule Design: Diversity-Based Comparison of Goal-Directed Generators
Journal of Chemical Information and Modeling·2024· 9 citedOpen Access
Improving Clinical Predictions with Multi-Modal Pre-training in Retinal Imaging
2024
xLSTM: Extended Long Short-Term Memory
arXiv (Cornell University)·2024· 84 citedOpen Access
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification
arXiv (Cornell University)·2024· 5 citedOpen Access
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks
arXiv (Cornell University)·2024· 1 citedOpen Access
HyperPCM: Robust Task-Conditioned Modeling of Drug–Target Interactions
Journal of Chemical Information and Modeling·2024· 14 citedOpen Access
xLSTM: Extended Long Short-Term Memory
2024· 13 cited
Principled Weight Initialisation for Input-Convex Neural Networks
arXiv (Cornell University)·2023· 1 citedOpen Access
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Frequent Co-authors

Sepp Hochreiter(40), Thomas Unterthiner(11), Andreas Mayr(8), Hubert Ramsauer(8), Ola Engkvist(6), Hongming Chen(6), Michael Widrich(6), Jörg K. Wegner(5), Daniel Klotz(5), Frederik Kratzert(5), J. Brandstetter(5), Michael Kopp(5), Elisabeth Rumetshofer(5), Milena Pavlović(5), Geir Kjetil Sandve(5), Victor Greiff(5), Djork-Arné Clevert(4), Bernhard Nessler(4), Grey Nearing(4), Rocío Mercado(4)