| Few-shot learning with graph neural networks G Victor, B Joan Proc. Int. Conf. Learn. Represent., 1-13, 2018 | 1472* | 2018 |
| E (n) equivariant graph neural networks VG Satorras, E Hoogeboom, M Welling International conference on machine learning, 9323-9332, 2021 | 666 | 2021 |
| Equivariant diffusion for molecule generation in 3d E Hoogeboom, VG Satorras, C Vignac, M Welling International conference on machine learning, 8867-8887, 2022 | 386 | 2022 |
| E (n) equivariant normalizing flows V Garcia Satorras, E Hoogeboom, F Fuchs, I Posner, M Welling Advances in Neural Information Processing Systems 34, 4181-4192, 2021 | 149 | 2021 |
| Neural enhanced belief propagation on factor graphs VG Satorras, M Welling International Conference on Artificial Intelligence and Statistics, 685-693, 2021 | 97 | 2021 |
| Equivariant 3D-conditional diffusion model for molecular linker design I Igashov, H Stärk, C Vignac, A Schneuing, VG Satorras, P Frossard, ... Nature Machine Intelligence, 1-11, 2024 | 75 | 2024 |
| Combining generative and discriminative models for hybrid inference VG Satorras, Z Akata, M Welling arXiv preprint arXiv:1906.02547, 2019 | 57* | 2019 |
| Two for one: Diffusion models and force fields for coarse-grained molecular dynamics M Arts, V Garcia Satorras, CW Huang, D Zügner, M Federici, C Clementi, ... Journal of Chemical Theory and Computation 19 (18), 6151-6159, 2023 | 39 | 2023 |
| The convolution exponential and generalized sylvester flows E Hoogeboom, V Garcia Satorras, J Tomczak, M Welling Advances in Neural Information Processing Systems 33, 18249-18260, 2020 | 29 | 2020 |
| Multivariate time series forecasting with latent graph inference VG Satorras, SS Rangapuram, T Januschowski arXiv preprint arXiv:2203.03423, 2022 | 20 | 2022 |
| Few-shot learning with graph neural networks. arXiv 2017 V Garcia, J Bruna arXiv preprint arXiv:1711.04043, 2017 | 20 | 2017 |
| Few-shot learning with graph neural networks. arXiv V Garcia, J Bruna arXiv preprint arXiv:1711.04043, 2017 | 13 | 2017 |
| A study of joint graph inference and forecasting D Zügner, FX Aubet, VG Satorras, T Januschowski, S Günnemann, ... arXiv preprint arXiv:2109.04979, 2021 | 12 | 2021 |
| International conference on machine learning VG Satorras, E Hoogeboom, M Welling PMLR,, 2021 | 11 | 2021 |
| Fast protein backbone generation with SE (3) flow matching J Yim, A Campbell, AYK Foong, M Gastegger, J Jiménez-Luna, S Lewis, ... arXiv preprint arXiv:2310.05297, 2023 | 8 | 2023 |
| E (n) equivariant graph neural networks V Garcia Satorras, E Hoogeboom, M Welling arXiv e-prints, arXiv: 2102.09844, 2021 | 4 | 2021 |
| Meta-learning with individualized feature space for few-shot classification V Garcia, J Bruna OpenReview, 2019 | 3 | 2019 |
| Control of a physical system based on inferred state VG Satorras, M Welling, V Fischer, Z Akata US Patent 11,620,517, 2023 | 2 | 2023 |
| As easy as APC: overcoming missing data and class imbalance in time series with self-supervised learning F Wever, TA Keller, L Symul, V Garcia arXiv preprint arXiv:2106.15577, 2021 | 1 | 2021 |
| Improved motif-scaffolding with SE (3) flow matching J Yim, A Campbell, E Mathieu, AYK Foong, M Gastegger, J Jiménez-Luna, ... arXiv preprint arXiv:2401.04082, 2024 | | 2024 |
