Publications

2023

T. Tschoellitsch, P. Seidl, C. Böck, A. Maletzky, P. Moser, S. Thumfart, M. Giretzlehner, S. Hochreiter, and J. Meier (2023) Using Emergency Department Triage for Machine Learning-Based Admission and Mortality Prediction. European Journal of Emergency Medicine, 2023-08-14. (more) (download)

J. Schimunek, P. Seidl, L. Friedrich, D. Kuhn, F. Rippmann, S. Hochreiter, and G. Klambauer (2023) Context-Enriched Molecule Representations Improve Few-Shot Drug Discovery. arXiv:2305.09481, 2023-04-24. (more) (download)

J. Schimunek, P. Seidl, K. Elez, T. Hempel, T. Le, F. Noé, S. Olsson, L. Raich, R. Winter, H. Gokcan, F. Gusev, E. M. Gutkin, O. Isayev, M. G. Kurnikova, C. H. Narangoda, R. Zubatyuk, I. P. Bosko, K. V. Furs, A. D. Karpenko, Y. V. Kornoushenko, M. Shuldau, A. Yushkevich, M. B. Benabderrahmane, P. Bousquet-Melou, R. Bureau, B. Charton, B. C. Cirou, G. Gil, W. J. Allen, S. Sirimulla, S. Watowich, N. A. Antonopoulos, N. E. Epitropakis, A. K. Krasoulis, V. P. Pitsikalis, S. T. Theodorakis, I. Kozlovskii, A. Maliutin, A. Medvedev, P. Popov, M. Zaretckii, H. Eghbal-zadeh, C. Halmich, S. Hochreiter, A. Mayr, P. Ruch, M. Widrich, F. Berenger, A. Kumar, Y. Yamanishi, K. YJ Zhang, E. Bengio, Y. Bengio, M. J. Jain, M. Korablyov, C.-H. Liu, G. Marcou, E. Glaab, K. Barnsley, S. M. Iyengar, M. Jo Ondrechen, V. J. Haupt, F. Kaiser, M. Schroeder, L. Pugliese, S. Albani, C. Athanasiou, A. Beccari, P. Carloni, G. D'Arrigo, E. Gianquinto, J. Goßen, A. Hanke, B. P. Joseph, D. B. Kokh, S. Kovachka, C. Manelfi, G. Mukherjee, A. Muñiz-Chicharro, F. Musiani, A. Nunes-Alves, G. Paiardi, G. Rossetti, S. K. Sadiq, F. Spyrakis, C. Talarico, A. Tsengenes, R. C. Wade, C. Copeland, J. Gaiser, D. R. Olson, A. Roy, V. Venkatraman, T. J. Wheeler, H. Arthanari, K. Blaschitz, M. Cespugli, V. Durmaz, K. Fackeldey, P. D. Fischer, C. Gorgulla, C. Gruber, K. Gruber, M. Hetmann, J. E. Kinney, K. M. P. Das, S. Pandita, A. Singh, G. Steinkellner, G. Tesseyre, G. Wagner, Z.-F. Wang, R. J. Yust, D. S. Druzhilovskiy, D. A. Filimonov, P. V. Pogodin, V. Poroikov, A. V. Rudik, L. A. Stolbov, A. V. Veselovsky, M. De Rosa, G. De Simone, M. R. Gulotta, J. Lombino, N. Mekni, U. Perricone, A. Casini, A. Embree, D. B. Gordon, D. Lei, K. Pratt, C. A. Voigt, K.-Y. Chen, Y. Jacob, T. Krischuns, P. Lafaye, A. Zettor, M. L. Rodríguez, K. M. White, D. Fearon, F. Von Delft, M. A. Walsh, D. Horvath, C. L. B. III, B. Falsafi, B. Ford, A. García-Sastre, S. Y. Lee, N. Naffakh, and A. Varnek (2023) A Community Effort to Discover Small Molecule SARS-CoV-2 Inhibitors. ChemRxiv, 2023-04-07. (more) (download)

P. Seidl, A. Vall, S. Hochreiter, and G. Klambauer (2023) Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language. arXiv:2303.03363, 2023-03-06. (more) (download)

2022

P. A. Robert, R. Akbar, R. Frank, M. Pavlović, M. Widrich, I. Snapkov, A. Slabodkin, M. Chernigovskaya, L. Scheffer, E. Smorodina, P. Rawat, B. B. Mehta, M. Ha Vu, I. F. Mathisen, A. Prósz, K. Abram, A. Olar, E. Miho, D. T. T. Haug, F. Lund-Johansen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2022) Unconstrained Generation of Synthetic Antibody–Antigen Structures to Guide Machine Learning Methodology for Antibody Specificity Prediction. Nature Computational Science, 2, 12, 845-865, 2022-12-19. (more) (download)

A. Sanchez-Fernandez, E. Rumetshofer, S. Hochreiter, and G. Klambauer (2022) CLOOME: Contrastive Learning Unlocks Bioimaging Databases for Queries with Chemical Structures. bioRxiv 2022.11.17.516915, 2022-11-18. (more) (download)

A. Maletzky, C. Böck, T. Tschoellitsch, T. Roland, H. Ludwig, S. Thumfart, M. Giretzlehner, S. Hochreiter, and J. Meier (2022) Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities. JMIR Medical Informatics, 10, 10, e38557, 2022-10-21. (more) (download)

A. Sanchez-Fernandez, E. Rumetshofer, S. Hochreiter, and G. Klambauer (2022) Contrastive Learning of Image- and Structure-based Representations in Drug Discovery. ICLR 2022 Machine Learning for Drug Discovery, 2022-04-29. (more) (download)

R. Akbar, P. A. Robert, C. R. Weber, M. Widrich, R. Frank, M. Pavlović, L. Scheffer, M. Chernigovskaya, I. Snapkov, A. Slabodkin, B. B. Mehta, E. Miho, F. Lund-Johansen, J. T. Andersen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2022) In Silico Proof of Principle of Machine Learning-Based Antibody Design at Unconstrained Scale. mAbs, 14, 1, 2031482, 2022-04-04. (more) (download)

T. Roland, C. Boeck, T. Tschoellitsch, A. Maletzky, S. Hochreiter, J. Meier, and G. Klambauer (2022) Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. Journal of Medical Systems, 46, 5, 23, 2022-03-29. (more) (download)

P. Seidl, P. Renz, N. Dyubankova, P. Neves, J. Verhoeven, J. K. Wegner, M. Segler, S. Hochreiter, and a. G. Klambauer (2022) Improving Few- and Zero-Shot Reaction Template Prediction Using Modern Hopfield Networks. Journal of Chemical Information and Modeling, 62, 9, 2111, 2022-01-15. (more) (download)

K. M. Trentino, K. Schwarzbauer, A. Mitterecker, A. Hofmann, A. Lloyd, M. F. Leahy, T. Tschoellitsch, C. Böck, S. Hochreiter, and J. Meier (2022) Machine Learning-Based Mortality Prediction of Patients at Risk During Hospital Admission. Journal of Patient Safety, 18, 5, 494-498, 2022-01-12. (more) (download)

2021

C. Shen, M. Krenn, S. Eppel, and A. Aspuru-Guzik (2021) Deep Molecular Dreaming: Inverse Machine Learning for De-novo Molecular Design and Interpretability with Surjective Representations. Machine Learning: Science and Technology, 2, 3, 03LT02, 2021-07-13. (more) (download)

P. A. Robert, R. Akbar, R. Frank, M. Pavlović, M. Widrich, I. Snapkov, M. Chernigovskaya, L. Scheffer, A. Slabodkin, B. B. Mehta, M. Ha Vu, A. Prósz, K. Abram, A. Olar, E. Miho, D. T. T. Haug, F. Lund-Johansen, S. Hochreiter, I. H. Haff, G. Klambauer, G. K. Sandve, and V. Greiff (2021) One Billion Synthetic 3D-Antibody-Antigen Complexes Enable Unconstrained Machine-Learning Formalized Investigation of Antibody Specificity Prediction. bioRxiv, 2021.07. 06.451258, 2021-07-11. (more) (download)

A. Vall, Y. Sabnis, J. Shi, R. Class, S. Hochreiter, and G. Klambauer (2021) The Promise of AI for DILI Prediction. Frontiers in Artificial Intelligence, 4, 638410, 2021-04-14. (more) (download)

M. Pavlovic, L. Scheffer, K. Motwani, C. Kanduri, R. Kompova, N. Vazov, K. Waagan, F. LM Bernal, A. A. Costa, B. Corrie, R. Akbar, G. S. Al Hajj, G. Balaban, T. M. Brusko, M. Chernigovskaya, S. Christley, L. G. Cowell, R. Frank, I. Grytten, S. Gundersen, I. H. Haff, S. Hochreiter, E. Hovig, P.-H. Hsieh, G. Klambauer, M. L. Kuijjer, C. Lund-Andersen, A. Martini, T. Minotto, J. Pensar, K. Rand, E. Riccardi, P. A. Robert, A. Rocha, A. Slabodkin, I. Snapkov, L. M. Sollid, D. Titov, C. R. Weber, M. Widrich, G. Yaari, V. Greiff, and G. K. Sandve (2021) immuneML: an Ecosystem for Machine Learning Analysis of Adaptive Immune Receptor Repertoires. bioRxiv, 2021-03-15. (more) (download)

2020

S. Kimeswenger, P. Tschandl, P. Noack, M. Hofmarcher, E. Rumetshofer, H. Kindermann, R. Silye, S. Hochreiter, M. Kaltenbrunner, E. Guenova, G. Klambauer, and W. Hoetzenecker (2020) Artificial neural networks and pathologists recognize basal cell carcinomas based on different histological patterns. Modern Pathology, 34, 5, 895–903, 2020-11-13. (more) (download)

P. Renz, D. Van Rompaey, J. K. Wegner, S. Hochreiter, and G. Klambauer (2020) On failure modes in molecule generation and optimization. Drug Discovery Today: Technologies, 32, 55-63, 2020-10-24. (more) (download)

M. Widrich, B. Schäfl, H. Ramsauer, M. Pavlović, L. Gruber, M. Holzleitner, J. Brandstetter, G. K. Sandve, V. Greiff, S. Hochreiter, and G. Klambauer (2020) Modern Hopfield Networks and Attention for Immune Repertoire Classification. arXiv:2007.13505, 2020-07-16. (more) (download)

A. Mitterecker, A. Hofmann, K. M. Trentino, A. Lloyd, M. F. Leahy, K. Schwarzbauer, T. Tschoellitsch, C. Böck, S. Hochreiter, and J. Meier (2020) Machine learning–based prediction of transfusion. Transfusion, 60, 1977–1986, 2020-06-28. (more) (download)

N. Sturm, A. Mayr, T. Le Van, V. Chupakhin, H. Ceulemans, J. Wegner, J.-F. Golib-Dzib, N. Jeliazkova, Y. Vandriessche, S. Böhm, V. Cima, J. Martinovic, N. Greene, T. V. Aa, T. J. Ashby, S. Hochreiter, O. Engkvist, G. Klambauer, and H. Chen (2020) Industry-scale application and evaluation of deep learning for drug target prediction. Journal of Cheminformatics, 12, 1-13, 2020-04-19. (more) (download)

M. Hofmarcher, A. Mayr, E. Rumetshofer, P. Ruch, P. Renz, J. Schimunek, P. Seidl, A. Vall, M. Widrich, S. Hochreiter, and G. Klambauer (2020) Large-Scale Ligand-Based Virtual Screening for SARS-CoV-2 Inhibitors Using Deep Neural Networks. SSRN 3561442, 2020-03-23. (more) (download)

A. Mayr, G. Klambauer, T. Unterthiner, and S. Hochreiter (2020) The LSC Benchmark Dataset: Technical Appendix and Partial Reanalysis. 2020-02-12. (more) (download)

2019

S. Kimeswenger, E. Rumetshofer, M. Hofmarcher, P. Tschandl, H. Kittler, S. Hochreiter, W. Hötzenecker, and G. Klambauer (2019) Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images. ML4H: Machine Learning for Health workshop at NeurIPS 2019, Vancouver, 10-12 Dec 2019, or preprint at arXiv, 1911.06616v3, Image and Video Processing (eess.IV), 2019-12-02. (more) (download)

K. Preuer, G. Klambauer, F. Rippmann, S. Hochreiter, and T. Unterthiner (2019) Interpretable Deep Learning in Drug Discovery. in Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, Springer, 331, 2019-09-10; preprint at arXiv, 1903.02788v2. (more) (download)

M. P. Menden, D. Wang, M. J. Mason, B. Szalai, K. C. Bulusu, Y. Guan, T. Yu, J. Kang, M. Jeon, R. Wolfinger, T. Nguyen, M. Zaslavskiy, A.-S. D. C. D. Consortium, I. S. Jang, Z. Ghazoui, M. E. Ahsen, R. Vogel, E. C. Neto, T. Norman, E. K. Y. Tang, M. J. Garnett, G. Y. Di Veroli, S. Fawell, G. Stolovitzky, J. Guinney, J. R. Dry, and J. Saez-Rodriguez (2019) Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nature Communications, 10, 2674, 2019-06-17. (more) (download)

G. Klambauer, S. Hochreiter, and M. Rarey (2019) Machine Learning in Drug Discovery. Journal of Chemical Information and Modeling , 59, 3, 945, 2019-03-25. (more) (download)

M. Hofmarcher, E. Rumetshofer, D.-A. Clevert, S. Hochreiter, and G. Klambauer (2019) Accurate prediction of biological assays with high-throughput microscopy images and convolutional networks. Journal of Chemical Information and Modeling, 59, 3, 1163, 2019-03-06. (more) (download)

E. Rumetshofer, M. Hofmarcher, C. Röhrl, S. Hochreiter, and G. Klambauer (2019) Human-level Protein Localization with Convolutional Neural Networks. International Conference on Learning Representations, ICLR 2019, New Orleans, 6-9 May. (more) (download)

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