| Hopfield networks is all you need H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ... arXiv preprint arXiv:2008.02217, 2020 | 421 | 2020 |
| Speeding up semantic segmentation for autonomous driving M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ... | 330 | 2016 |
| Rudder: Return decomposition for delayed rewards JA Arjona-Medina, M Gillhofer, M Widrich, T Unterthiner, J Brandstetter, ... Advances in Neural Information Processing Systems 32, 2018 | 227 | 2018 |
| Modern Hopfield Networks and Attention for Immune Repertoire Classification GK Michael Widrich, Bernhard Schäfl, Hubert Ramsauer, Milena Pavlović, Lukas ... Advances in Neural Information Processing Systems 33, 18832-18845, 2020 | 113 | 2020 |
| Explaining and interpreting LSTMs L Arras, J Arjona-Medina, M Widrich, G Montavon, M Gillhofer, KR Müller, ... Explainable ai: Interpreting, explaining and visualizing deep learning, 211-238, 2019 | 101 | 2019 |
| In silico proof of principle of machine learning-based antibody design at unconstrained scale R Akbar, PA Robert, CR Weber, M Widrich, R Frank, M Pavlović, ... MAbs 14 (1), 2031482, 2022 | 84 | 2022 |
| The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires M Pavlović, L Scheffer, K Motwani, C Kanduri, R Kompova, N Vazov, ... Nature Machine Intelligence 3 (11), 936-944, 2021 | 59 | 2021 |
| Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks M Hofmarcher, A Mayr, E Rumetshofer, P Ruch, P Renz, J Schimunek, ... arXiv preprint arXiv:2004.00979, 2020 | 59 | 2020 |
| Cross-domain few-shot learning by representation fusion T Adler, J Brandstetter, M Widrich, A Mayr, D Kreil, MK Kopp, ... | 41 | 2020 |
| Unconstrained generation of synthetic antibody–antigen structures to guide machine learning methodology for antibody specificity prediction PA Robert, R Akbar, R Frank, M Pavlović, M Widrich, I Snapkov, ... Nature Computational Science 2 (12), 845-865, 2022 | 30 | 2022 |
| One billion synthetic 3D-antibody-antigen complexes enable unconstrained machine-learning formalized investigation of antibody specificity prediction PA Robert, R Akbar, R Frank, M Pavlović, M Widrich, I Snapkov, ... BioRXiV, 2021.07. 06.451258, 2021 | 24 | 2021 |
| Modern hopfield networks for return decomposition for delayed rewards M Widrich, M Hofmarcher, VP Patil, A Bitto-Nemling, S Hochreiter Deep RL Workshop NeurIPS 2021, 2021 | 18 | 2021 |
| DeepRC: immune repertoire classification with attention-based deep massive multiple instance learning M Widrich, B Schäfl, M Pavlović, GK Sandve, S Hochreiter, V Greiff, ... BioRxiv 2020, 038158, 2020 | 14 | 2020 |
| A community effort in SARS‐CoV‐2 drug discovery J Schimunek, P Seidl, K Elez, T Hempel, T Le, F Noé, S Olsson, L Raich, ... Molecular Informatics 43 (1), e202300262, 2024 | 2 | 2024 |
| Modern Hopfield networks for sample-efficient return decomposition from demonstrations M Widrich, M Hofmarcher, VP Patil, A Bitto-Nemling, S Hochreiter Offline Reinforcement Learning Workshop NeurIPS, 2021 | 1 | 2021 |
| A community effort to discover small molecule SARS-CoV-2 inhibitors J Schimunek, P Seidl, K Elez, T Hempel, T Le, F Noé, S Olsson, L Raich, ... American Chemical Society (ACS), 2023 | | 2023 |
| Deep Learning Methods for Credit Assignment in Reinforcement Learning and Immune Repertoire Classification/submitted by Michael Widrich M Widrich | | 2022 |
| Long Short-Term Memory and convolutional neural networks for SNV-based phenotype prediction/submitted by Michael Widrich M Widrich | | 2016 |
| SUPPLEMENT A: Modern Hopfield Networks and Attention for Immune Repertoire Classification M Widrich, B Schäfl, M Pavlovic, GK Sandve, S Hochreiter, V Greiff, ... | | |
| Michael Gillhofer2, Klaus-Robert Müller3, 4, 5, Sepp Hochreiter2, and Wojciech Samek1 L Arras, J Arjona-Medina, M Widrich, G Montavon | | |
