| Few-shot learning with graph neural networks G Victor, B Joan Proc. Int. Conf. Learn. Represent., 1-13, 2018 | 1569* | 2018 |
| E (n) equivariant graph neural networks VG Satorras, E Hoogeboom, M Welling International conference on machine learning, 9323-9332, 2021 | 829 | 2021 |
| Equivariant diffusion for molecule generation in 3d E Hoogeboom, VG Satorras, C Vignac, M Welling International conference on machine learning, 8867-8887, 2022 | 507 | 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 | 183 | 2021 |
| Neural enhanced belief propagation on factor graphs VG Satorras, M Welling International Conference on Artificial Intelligence and Statistics, 685-693, 2021 | 109 | 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 | 100 | 2024 |
| Combining generative and discriminative models for hybrid inference VG Satorras, Z Akata, M Welling arXiv preprint arXiv:1906.02547, 2019 | 61* | 2019 |
| Two for one: Diffusion models and force fields for coarse-grained molecular dynamics M Arts, V Garcia Satorras, CW Huang, D Zugner, M Federici, C Clementi, ... Journal of Chemical Theory and Computation 19 (18), 6151-6159, 2023 | 60 | 2023 |
| 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 | 31 | 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 | 31 | 2020 |
| Multivariate time series forecasting with latent graph inference VG Satorras, SS Rangapuram, T Januschowski arXiv preprint arXiv:2203.03423, 2022 | 22 | 2022 |
| Proceedings of the 38th International Conference on Machine Learning VG Satorras, E Hoogeboom, M Welling PMLR, Cambridge 139, 9323-9332, 2021 | 19 | 2021 |
| A study of joint graph inference and forecasting D Zügner, FX Aubet, VG Satorras, T Januschowski, S Günnemann, ... arXiv preprint arXiv:2109.04979, 2021 | 15 | 2021 |
| Improved motif-scaffolding with SE (3) flow matching J Yim, A Campbell, E Mathieu, AYK Foong, M Gastegger, J Jiménez-Luna, ... ArXiv, 2024 | 5 | 2024 |
| 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 | 2 | 2021 |
| Application of Generative AI as an Enterprise Wikibase Knowledge Graph Q&A System R Mendes, D Oliveira, V Garcia Proceedings of the 1st Workshop on Knowledge Graphs and Large Language …, 2024 | | 2024 |
| Inductive Biases for Graph Neural Networks VG Satorras Victor Garcia Satorras, 2024 | | 2024 |
| Method and apparatus using a graph neural network VG Satorras, E Hoogeboom, M Welling US Patent App. 17/649,297, 2022 | | 2022 |
