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Günter Klambauer
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2020 – today
- 2024
- [j16]Emma Svensson, Pieter-Jan Hoedt, Sepp Hochreiter, Günter Klambauer:
HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions. J. Chem. Inf. Model. 64(7): 2539-2553 (2024) - [j15]Philipp Renz, Sohvi Luukkonen, Günter Klambauer:
Diverse Hits in De Novo Molecule Design: Diversity-Based Comparison of Goal-Directed Generators. J. Chem. Inf. Model. 64(15): 5756-5761 (2024) - [c15]Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr:
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks. Tiny Papers @ ICLR 2024 - [c14]Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri, Milena Pavlovic, Knut Dagestad Rand, Michael Widrich, Anne H. Schistad Solberg, Victor Greiff, Johan Pensar, Günter Klambauer, Geir Kjetil Sandve:
Incorporating probabilistic domain knowledge into deep multiple instance learning. ICML 2024 - [c13]Emese Sükei, Elisabeth Rumetshofer, Niklas Schmidinger, Andreas Mayr, Ursula Schmidt-Erfurth, Günter Klambauer, Hrvoje Bogunovic:
Improving Clinical Predictions with Multi-Modal Pre-training in Retinal Imaging. ISBI 2024: 1-5 - [i24]Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr:
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks. CoRR abs/2403.04747 (2024) - [i23]Florian Sestak, Lisa Schneckenreiter, Johannes Brandstetter, Sepp Hochreiter, Andreas Mayr, Günter Klambauer:
VN-EGNN: E(3)-Equivariant Graph Neural Networks with Virtual Nodes Enhance Protein Binding Site Identification. CoRR abs/2404.07194 (2024) - [i22]Maximilian Beck, Korbinian Pöppel, Markus Spanring, Andreas Auer, Oleksandra Prudnikova, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
xLSTM: Extended Long Short-Term Memory. CoRR abs/2405.04517 (2024) - 2023
- [c12]Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer:
Context-enriched molecule representations improve few-shot drug discovery. ICLR 2023 - [c11]Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer:
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. ICML 2023: 30458-30490 - [c10]Pieter-Jan Hoedt, Günter Klambauer:
Principled Weight Initialisation for Input-Convex Neural Networks. NeurIPS 2023 - [c9]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter:
Quantification of Uncertainty with Adversarial Models. NeurIPS 2023 - [i21]Philipp Seidl, Andreu Vall, Sepp Hochreiter, Günter Klambauer:
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. CoRR abs/2303.03363 (2023) - [i20]Johannes Schimunek, Philipp Seidl, Lukas Friedrich, Daniel Kuhn, Friedrich Rippmann, Sepp Hochreiter, Günter Klambauer:
Context-enriched molecule representations improve few-shot drug discovery. CoRR abs/2305.09481 (2023) - [i19]Kajetan Schweighofer, Lukas Aichberger, Mykyta Ielanskyi, Günter Klambauer, Sepp Hochreiter:
Quantification of Uncertainty with Adversarial Models. CoRR abs/2307.03217 (2023) - [i18]Pieter-Jan Hoedt, Günter Klambauer:
Principled Weight Initialisation for Input-Convex Neural Networks. CoRR abs/2312.12474 (2023) - 2022
- [j14]Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Marwin H. S. Segler, Sepp Hochreiter, Günter Klambauer:
Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. J. Chem. Inf. Model. 62(9): 2111-2120 (2022) - [j13]Theresa Roland, Carl Böck, Thomas Tschoellitsch, Alexander Maletzky, Sepp Hochreiter, Jens Meier, Günter Klambauer:
Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. J. Medical Syst. 46(5): 23 (2022) - [j12]Philippe A. Robert, Rahmad Akbar, Robert Frank, Milena Pavlovic, Michael Widrich, Igor Snapkov, Andrei Slabodkin, Maria Chernigovskaya, Lonneke Scheffer, Eva Smorodina, Puneet Rawat, Brij Bhushan Mehta, Mai Ha Vu, Ingvild Frøberg Mathisen, Aurél Prósz, Krzysztof Abram, Alex Olar, Enkelejda Miho, Dag Trygve Truslew Haug, Fridtjof Lund-Johansen, Sepp Hochreiter, Ingrid Hobæk Haff, Günter Klambauer, Geir Kjetil Sandve, Victor Greiff:
Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction. Nat. Comput. Sci. 2(12): 845-865 (2022) - [c8]Andreas Fürst, Elisabeth Rumetshofer, Johannes Lehner, Viet T. Tran, Fei Tang, Hubert Ramsauer, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto, Sepp Hochreiter:
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. NeurIPS 2022 - 2021
- [j11]Andreu Vall, Yogesh Sabnis, Jiye Shi, Reiner Class, Sepp Hochreiter, Günter Klambauer:
The Promise of AI for DILI Prediction. Frontiers Artif. Intell. 4: 638410 (2021) - [j10]Rocío Mercado, Tobias Rastemo, Edvard Lindelöf, Günter Klambauer, Ola Engkvist, Hongming Chen, Esben Jannik Bjerrum:
Graph networks for molecular design. Mach. Learn. Sci. Technol. 2(2): 25023 (2021) - [j9]Milena Pavlovic, Lonneke Scheffer, Keshav Motwani, Chakravarthi Kanduri, Radmila Kompova, Nikolay Vazov, Knut Waagan, Fabian L. M. Bernal, Alexandre Almeida Costa, Brian Corrie, Rahmad Akbar, Ghadi S. Al Hajj, Gabriel Balaban, Todd M. Brusko, Maria Chernigovskaya, Scott Christley, Lindsay G. Cowell, Robert Frank, Ivar Grytten, Sveinung Gundersen, Ingrid Hobæk Haff, Eivind Hovig, Ping-Han Hsieh, Günter Klambauer, Marieke L. Kuijjer, Christin Lund-Andersen, Antonio Martini, Thomas Minotto, Johan Pensar, Knut D. Rand, Enrico Riccardi, Philippe A. Robert, Artur Rocha, Andrei Slabodkin, Igor Snapkov, Ludvig Magne Sollid, Dmytro Titov, Cédric R. Weber, Michael Widrich, Gur Yaari, Victor Greiff, Geir Kjetil Sandve:
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires. Nat. Mach. Intell. 3(11): 936-944 (2021) - [c7]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Thomas Adler, David P. Kreil, Michael K. Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. ICLR 2021 - [c6]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. ICML 2021: 4275-4286 - [i17]Pieter-Jan Hoedt, Frederik Kratzert, Daniel Klotz, Christina Halmich, Markus Holzleitner, Grey Nearing, Sepp Hochreiter, Günter Klambauer:
MC-LSTM: Mass-Conserving LSTM. CoRR abs/2101.05186 (2021) - [i16]Philipp Seidl, Philipp Renz, Natalia Dyubankova, Paulo Neves, Jonas Verhoeven, Jörg K. Wegner, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks for Few- and Zero-Shot Reaction Prediction. CoRR abs/2104.03279 (2021) - [i15]Andreas Fürst, Elisabeth Rumetshofer, Viet Tran, Hubert Ramsauer, Fei Tang, Johannes Lehner, David P. Kreil, Michael Kopp, Günter Klambauer, Angela Bitto-Nemling, Sepp Hochreiter:
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP. CoRR abs/2110.11316 (2021) - 2020
- [j8]Noé Sturm, Andreas Mayr, Thanh Le Van, Vladimir I. Chupakhin, Hugo Ceulemans, Jörg K. Wegner, José Felipe Golib Dzib, Nina Jeliazkova, Yves Vandriessche, Stanislav Böhm, Vojtech Cima, Jan Martinovic, Nigel Greene, Tom Vander Aa, Thomas J. Ashby, Sepp Hochreiter, Ola Engkvist, Günter Klambauer, Hongming Chen:
Industry-scale application and evaluation of deep learning for drug target prediction. J. Cheminformatics 12(1): 26 (2020) - [c5]Michael Widrich, Bernhard Schäfl, Milena Pavlovic, Hubert Ramsauer, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. NeurIPS 2020 - [i14]Markus Hofmarcher, Andreas Mayr, Elisabeth Rumetshofer, Peter Ruch, Philipp Renz, Johannes Schimunek, Philipp Seidl, Andreu Vall, Michael Widrich, Sepp Hochreiter, Günter Klambauer:
Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks. CoRR abs/2004.00979 (2020) - [i13]Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlovic, Lukas Gruber, Markus Holzleitner, Johannes Brandstetter, Geir Kjetil Sandve, Victor Greiff, Sepp Hochreiter, Günter Klambauer:
Modern Hopfield Networks and Attention for Immune Repertoire Classification. CoRR abs/2007.13505 (2020) - [i12]Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Lukas Gruber, Markus Holzleitner, Milena Pavlovic, Geir Kjetil Sandve, Victor Greiff, David P. Kreil, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter:
Hopfield Networks is All You Need. CoRR abs/2008.02217 (2020) - [i11]Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David P. Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter:
Cross-Domain Few-Shot Learning by Representation Fusion. CoRR abs/2010.06498 (2020) - [i10]Daniel Klotz, Frederik Kratzert, Martin Gauch, Alden Keefe Sampson, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Uncertainty Estimation with Deep Learning for Rainfall-Runoff Modelling. CoRR abs/2012.14295 (2020)
2010 – 2019
- 2019
- [j7]Günter Klambauer, Sepp Hochreiter, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 59(3): 945-946 (2019) - [j6]Noé Sturm, Jiangming Sun, Yves Vandriessche, Andreas Mayr, Günter Klambauer, Lars Carlsson, Ola Engkvist, Hongming Chen:
Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models. J. Chem. Inf. Model. 59(3): 962-972 (2019) - [j5]Markus Hofmarcher, Elisabeth Rumetshofer, Djork-Arné Clevert, Sepp Hochreiter, Günter Klambauer:
Accurate Prediction of Biological Assays with High-Throughput Microscopy Images and Convolutional Networks. J. Chem. Inf. Model. 59(3): 1163-1171 (2019) - [c4]Elisabeth Rumetshofer, Markus Hofmarcher, Clemens Röhrl, Sepp Hochreiter, Günter Klambauer:
Human-level Protein Localization with Convolutional Neural Networks. ICLR (Poster) 2019 - [p4]Markus Hofmarcher, Thomas Unterthiner, Jose A. Arjona-Medina, Günter Klambauer, Sepp Hochreiter, Bernhard Nessler:
Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. Explainable AI 2019: 285-296 - [p3]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. Explainable AI 2019: 331-345 - [p2]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. Explainable AI 2019: 347-362 - [i9]Kristina Preuer, Günter Klambauer, Friedrich Rippmann, Sepp Hochreiter, Thomas Unterthiner:
Interpretable Deep Learning in Drug Discovery. CoRR abs/1903.02788 (2019) - [i8]Frederik Kratzert, Mathew Herrnegger, Daniel Klotz, Sepp Hochreiter, Günter Klambauer:
NeuralHydrology - Interpreting LSTMs in Hydrology. CoRR abs/1903.07903 (2019) - [i7]Frederik Kratzert, Daniel Klotz, Guy Shalev, Günter Klambauer, Sepp Hochreiter, Grey Nearing:
Benchmarking a Catchment-Aware Long Short-Term Memory Network (LSTM) for Large-Scale Hydrological Modeling. CoRR abs/1907.08456 (2019) - [i6]Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher, Philipp Tschandl, Harald Kittler, Sepp Hochreiter, Wolfram Hötzenecker, Günter Klambauer:
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. CoRR abs/1911.06616 (2019) - 2018
- [j4]Kristina Preuer, Richard P. I. Lewis, Sepp Hochreiter, Andreas Bender, Krishna C. Bulusu, Günter Klambauer:
DeepSynergy: predicting anti-cancer drug synergy with Deep Learning. Bioinform. 34(9): 1538-1546 (2018) - [j3]Sepp Hochreiter, Günter Klambauer, Matthias Rarey:
Machine Learning in Drug Discovery. J. Chem. Inf. Model. 58(9): 1723-1724 (2018) - [j2]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemNet Distance: A Metric for Generative Models for Molecules in Drug Discovery. J. Chem. Inf. Model. 58(9): 1736-1741 (2018) - [c3]Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. ICLR (Poster) 2018 - [i5]Kristina Preuer, Philipp Renz, Thomas Unterthiner, Sepp Hochreiter, Günter Klambauer:
Fréchet ChemblNet Distance: A metric for generative models for molecules. CoRR abs/1803.09518 (2018) - 2017
- [c2]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. NIPS 2017: 971-980 - [i4]Günter Klambauer, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Self-Normalizing Neural Networks. CoRR abs/1706.02515 (2017) - [i3]Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Sepp Hochreiter:
GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium. CoRR abs/1706.08500 (2017) - [i2]Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter:
Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. CoRR abs/1708.08819 (2017) - 2015
- [j1]Günter Klambauer, Martin Wischenbart, Michael Mahr, Thomas Unterthiner, Andreas Mayr, Sepp Hochreiter:
Rchemcpp: a web service for structural analoging in ChEMBL, Drugbank and the Connectivity Map. Bioinform. 31(20): 3392-3394 (2015) - [i1]Thomas Unterthiner, Andreas Mayr, Günter Klambauer, Sepp Hochreiter:
Toxicity Prediction using Deep Learning. CoRR abs/1503.01445 (2015) - 2014
- [b1]Günter Klambauer:
Machine Learning Techniques for the Analysis of High-Throughput DNA and RNA Sequencing Data. Universität Linz, 2014, pp. I-XXII, 1-184 - [p1]Günter Klambauer:
Techniken des maschinellen Lernens zur Analyse von Hochdurchsatz-DNA- und RNA-Sequenzierungsdaten. Ausgezeichnete Informatikdissertationen 2014: 131-140 - 2012
- [c1]Tor Johan Mikael Karlsson, Óscar Torreño Tirado, Daniel Ramet Barea, Günter Klambauer, Miriam Cano Castillo, Oswaldo Trelles:
Enabling Large-Scale Bioinformatics Data Analysis with Cloud Computing. ISPA 2012: 640-645
Coauthor Index
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last updated on 2024-10-07 01:19 CEST by the dblp team
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