Günter Klambauer

7.7k citations

45 papers · 3.1k indexed · 3 hit papers · h-index 24

Computational Theory and Mathematics top 0.2%
Molecular Biology top 5%
Materials Chemistry top 5%
Artificial Intelligence top 5%
Genetics top 10%

Co-authors: Sepp Hochreiter Andreas Mayr Thomas Unterthiner Djork-Arné Clevert Jörg K. Wegner Kristina Preuer Andreas Bender Richard P. Lewis
Topics: Computational Drug Discovery Methods (21 papers)Machine Learning in Materials Science (14 papers)Protein Structure and Dynamics (7 papers)
Cited by: Computational Theory and Mathematics Biophysics Health Informatics
Journals: Nucleic Acids Research Nature CommunicationsSHILAP Revista de lepidopterología
Partner nations: Austria United States Belgium

In The Last Decade

Günter Klambauer

44 papers receiving 3.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

DeepTox: Toxicity Prediction using Deep Learning

2016 638 citations Andreas Mayr, Günter Klambauer et al. profile →
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning

2017 382 citations Kristina Preuer, Sepp Hochreiter et al. profile →
Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

2018 352 citations Andreas Mayr, Günter Klambauer et al. profile →

Peers

Countries citing papers authored by Günter Klambauer

Since Specialization

Citations

This map shows the geographic impact of Günter Klambauer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Günter Klambauer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Günter Klambauer more than expected).

Fields of papers citing papers by Günter Klambauer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Günter Klambauer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Günter Klambauer. The network helps show where Günter Klambauer may publish in the future.

Co-authorship network of co-authors of Günter Klambauer

This figure shows the co-authorship network connecting the top 25 collaborators of Günter Klambauer. A scholar is included among the top collaborators of Günter Klambauer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Günter Klambauer. Günter Klambauer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	VN-EGNN: E(3)- and SE(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification 2025 ·Journal of Cheminformatics ·(unknown),(unknown),J. Brandstetter,Sepp Hochreiter,Andreas Mayr,Günter Klambauer	0
2	CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures 2023 ·Nature Communications ·(unknown),(unknown),Sepp Hochreiter,Günter Klambauer	24
3	Uncertainty estimation with deep learning for rainfall–runoff modeling 2022 ·Hydrology and earth system sciences ·Daniel Klotz,Frederik Kratzert,Martin Gauch,Alden Keefe Sampson,J. Brandstetter,Günter Klambauer,Sepp Hochreiter,Grey Nearing	104
4	In silico proof of principle of machine learning-based antibody design at unconstrained scale 2022 ·mAbs ·Rahmad Akbar,Philippe A. Robert,Cédric R. Weber,Michael Widrich,(unknown),Milena Pavlović,Lonneke Scheffer,Maria Chernigovskaya,Igor Snapkov,Andrei Slabodkin,Brij Bhushan Mehta,Enkelejda Miho,Fridtjof Lund‐Johansen,Jan Terje Andersen,Sepp Hochreiter,Ingrid Hobæk Haff,Günter Klambauer,Geir Kjetil Sandve,Victor Greiff	50
5	Uncertainty Estimation with Deep Learning for Rainfall–Runoff Modelling 2021 ·Daniel Klotz,Frederik Kratzert,Martin Gauch,Alden Keefe Sampson,J. Brandstetter,Günter Klambauer,Sepp Hochreiter,Grey Nearing	13
6	Uncertainty estimation with LSTM based rainfall-runoff models 2021 ·Daniel Klotz,Frederik Kratzert,Martin Gauch,Alden Keefe Sampson,Günter Klambauer,J. Brandstetter,Sepp Hochreiter,Grey Nearing	1
7	Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. 2021 ·arXiv (Cornell University) ·Philipp Seidl,Philipp Renz,Natalia Dyubankova,(unknown),Jonas Verhoeven,Jörg K. Wegner,Sepp Hochreiter,Günter Klambauer	1
8	The Promise of AI for DILI Prediction 2021 ·Frontiers in Artificial Intelligence ·Andreu Vall,Yogesh Sabnis,Jiye Shi,Reiner Class,Sepp Hochreiter,Günter Klambauer	35
9	Graph networks for molecular design 2020 ·Machine Learning Science and Technology ·Rocío Mercado,(unknown),Edvard Lindelöf,Günter Klambauer,Ola Engkvist,Hongming Chen,Esben Jannik Bjerrum	102
10	Industry-scale application and evaluation of deep learning for drug target prediction 2020 ·Journal of Cheminformatics ·Noé Sturm,Andreas Mayr,(unknown),Vladimir Chupakhin,Hugo Ceulemans,Jörg K. Wegner,(unknown),Nina Jeliazkova,(unknown),Stanislav Böhm,(unknown),Jan Martinovič,Nigel Greene,Tom Vander Aa,Thomas J. Ashby,Sepp Hochreiter,Ola Engkvist,Günter Klambauer,Hongming Chen	29
11	Towards the quantification of uncertainty for deep learning based rainfall-runoff models 2019 ·EGU General Assembly Conference Abstracts ·Daniel Klotz,Frederik Kratzert,Mathew Herrnegger,Sepp Hochreiter,Günter Klambauer	1
12	On failure modes in molecule generation and optimization 2019 ·Drug Discovery Today Technologies ·Philipp Renz,Dries Van Rompaey,Jörg K. Wegner,Sepp Hochreiter,Günter Klambauer	86
13	Benchmarking a Catchment-Aware Long Short-Term MemoryNetwork (LSTM) for Large-Scale Hydrological Modeling 2019 ·arXiv (Cornell University) ·Frederik Kratzert,Daniel Klotz,Guy Shalev,Günter Klambauer,Sepp Hochreiter,Grey Nearing	18
14	Fréchet ChemblNet Distance: A metric for generative models for molecules. 2018 ·arXiv (Cornell University) ·Kristina Preuer,Philipp Renz,Thomas Unterthiner,Sepp Hochreiter,Günter Klambauer	2
15	Human-level Protein Localization with Convolutional Neural Networks 2018 ·International Conference on Learning Representations ·(unknown),Markus Hofmarcher,Clemens Röhrl,Sepp Hochreiter,Günter Klambauer	5
16	Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields 2018 ·International Conference on Learning Representations ·Thomas Unterthiner,Bernhard Nessler,(unknown),Günter Klambauer,Martin Heusel,Hubert Ramsauer,Sepp Hochreiter	6
17	Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery 2018 ·Cell chemical biology ·Jaak Simm,Günter Klambauer,Ádám Arany,Marvin Steijaert,Jörg K. Wegner,Emmanuel Gustin,Vladimir Chupakhin,Yolanda Chong,Jorge Vialard,Peter Buijnsters,Ingrid Velter,A. Vapirev,Shantanu Singh,Anne E. Carpenter,Roel Wuyts,Sepp Hochreiter,Yves Moreau,Hugo Ceulemans	140
18	The unfolded protein response impacts melanoma progression by enhancing FGF expression and can be antagonized by a chemical chaperone 2017 ·Scientific Reports ·(unknown),(unknown),(unknown),Birgit Schütz,Günter Klambauer,Richard Moriggl,Markus Hengstschläger,Herbert Stangl,Mario Mikula,Clemens Röhrl	24
19	How Adverse Outcome Pathways Can Aid the Development and Use of Computational Prediction Models for Regulatory Toxicology 2016 ·Toxicological Sciences ·Clemens Wittwehr,Hristo Aladjov,Gerald T. Ankley,Hugh J. Byrne,Joop de Knecht,Elmar Heinzle,Günter Klambauer,Brigitte Landesmann,Mirjam Luijten,Cameron MacKay,Gavin Maxwell,M.E. Meek,Alicia Paini,Edward J. Perkins,Tomasz Sobański,(unknown),Katrina M. Waters,Maurice Whelan	119
20	Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project 2015 ·Drug Discovery Today ·Bie Verbist,Günter Klambauer,(unknown),Willem Talloen,Ziv Shkedy,Olivier Thas,Andreas Bender,Hinrich W. H. Göhlmann,Sepp Hochreiter	63

About Günter Klambauer

Günter Klambauer is a scholar working on Computational Theory and Mathematics, Biophysics and Water Science and Technology, having authored 45 papers that have together received 3.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (21 papers), Machine Learning in Materials Science (14 papers) and Protein Structure and Dynamics (7 papers). The work is most often cited by research in Computational Theory and Mathematics (1.6k citations), Biophysics (278 citations) and Health Informatics (45 citations). Günter Klambauer has collaborated with scholars based in Austria, United States and Belgium. Frequent co-authors include Sepp Hochreiter, Andreas Mayr, Thomas Unterthiner, Djork-Arné Clevert, Jörg K. Wegner, Kristina Preuer, Andreas Bender, Richard P. Lewis, Krishna C. Bulusu and Hugo Ceulemans. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact