| 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 | 617 | 2020 |
| Modern hopfield networks and attention for immune repertoire classification M Widrich, B Schäfl, M Pavlović, H Ramsauer, L Gruber, M Holzleitner, ... Advances in neural information processing systems 33, 18832-18845, 2020 | 149 | 2020 |
| Convergence proof for actor-critic methods applied to PPO and RUDDER M Holzleitner, L Gruber, J Arjona-Medina, J Brandstetter, S Hochreiter Transactions on Large-Scale Data-and Knowledge-Centered Systems XLVIII …, 2021 | 47 | 2021 |
| Modern Hopfield networks as memory for iterative learning on tabular data B Schäfl, L Gruber, A Bitto-Nemling, S Hochreiter Associative Memory {\&} Hopfield Networks in 2023, 2023 | 32* | 2023 |
| Hopfield networks is all you need. arXiv 2020 H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ... arXiv preprint arXiv:2008.02217, 0 | 22 | |
| Universal physics transformers B Alkin, A Fürst, S Schmid, L Gruber, M Holzleitner, J Brandstetter arXiv e-prints, arXiv: 2402.12365, 2024 | 13 | 2024 |
| Universal physics transformers: A framework for efficiently scaling neural operators B Alkin, A Fürst, S Schmid, L Gruber, M Holzleitner, J Brandstetter Advances in Neural Information Processing Systems 37, 25152-25194, 2024 | 12 | 2024 |
| Overcoming saturation in density ratio estimation by iterated regularization L Gruber, M Holzleitner, J Lehner, S Hochreiter, W Zellinger arXiv preprint arXiv:2402.13891, 2024 | 4 | 2024 |
| Processing large-scale Graphs with G-Signatures L Gruber, B Schäfl, J Brandstetter, S Hochreiter ICML 2024 AI for Science Workshop, 0 | 4* | |
