| 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, 2024 | 11 | 2024 |
| BESS: Balanced entity sampling and sharing for large-scale knowledge graph completion A Cattaneo, D Justus, H Mellor, D Orr, J Maloberti, Z Liu, T Farnsworth, ... Conference on Neural Information Processing Systems, 2022 | 3 | 2022 |
| Reducing the cost of quantum chemical data by backpropagating through density functional theory A Mathiasen, H Helal, P Balanca, A Krzywaniak, A Parviz, F Hvilshøj, ... arXiv preprint arXiv:2402.04030, 2024 | 2 | 2024 |
| : A Parameter-Efficient Foundation Model for Molecular Learning K Kläser, B Banaszewski, S Maddrell-Mander, C McLean, L Müller, ... ICML Workshop on Accessible and Efficient Foundation Models for Biological …, 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 |
Alexander MathiasenPh. D. student, Aarhus University在 cs.au.dk 的电子邮件经过验证
