| Attending to Graph Transformers L Müller, M Galkin, C Morris, L Rampášek Transactions of Machine Learning Research, 2023 | 72 | 2023 |
| Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets D Beaini, S Huang, JA Cunha, G Moisescu-Pareja, O Dymov, ... International Conference on Learning Representations, 2023 | 12 | 2023 |
| On reachable assignments in cycles and cliques L Müller, M Bentert arXiv preprint arXiv:2005.02218, 2020 | 6 | 2020 |
| On Reachable Assignments in Cycles L Müller, M Bentert Algorithmic Decision Theory: 7th International Conference, ADT 2021 …, 2021 | 3 | 2021 |
| Aligning Transformers with Weisfeiler-Leman L Müller, C Morris International Conference on Machine Learning, 2024 | | 2024 |
| : A Parameter-Efficient Foundation Model for Molecular Learning K Kläser, B Banaszewski, S Maddrell-Mander, C McLean, L Müller, ... arXiv preprint arXiv:2404.14986, 2024 | | 2024 |
| Towards Principled Graph Transformers L Müller, C Morris arXiv preprint arXiv:2401.10119, 2024 | | 2024 |
| MiniMol: A Parameter-Efficient Foundation Model for Molecular Learning K Klaser, B Banaszewski, S Maddrell-Mander, C McLean, L Müller, ... ICML 2024 Workshop on Efficient and Accessible Foundation Models for …, 2024 | | 2024 |
Christopher MorrisRWTH Aachen UniversityVerified email at cs.rwth-aachen.de
