| VACA: Designing variational graph autoencoders for causal queries P Sánchez-Martin, M Rateike, I Valera Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 8159-8168, 2022 | 28* | 2022 |
| Learnable graph convolutional attention networks A Javaloy, P Sanchez-Martin, A Levi, I Valera arXiv preprint arXiv:2211.11853, 2022 | 13 | 2022 |
| Causal normalizing flows: from theory to practice A Javaloy, P Sánchez-Martín, I Valera Advances in Neural Information Processing Systems 36, 2024 | 10 | 2024 |
| Improved BiGAN training with marginal likelihood equalization P Sánchez-Martín, PM Olmos, F Perez-Cruz arXiv preprint arXiv:1911.01425, 2019 | 3 | 2019 |
| Variational mixture of hypergenerators for learning distributions over functions B Koyuncu, P Sanchez-Martin, I Peis, PM Olmos, I Valera arXiv preprint arXiv:2302.06223, 2023 | 2 | 2023 |
| Improving the interpretability of GNN predictions through conformal-based graph sparsification P Sanchez-Martin, KA Khan, I Valera arXiv preprint arXiv:2404.12356, 2024 | 1 | 2024 |
| Enhancing diversity in GANs via non-uniform sampling P Sánchez-Martín, PM Olmos, F Perez-Cruz Information Sciences 637, 118928, 2023 | 1 | 2023 |
| Out-of-sample testing for gans P Sánchez-Martín, PM Olmos, F Pérez-Cruz arXiv preprint arXiv:1901.09557, 2019 | 1 | 2019 |
| Unsupervised deep learning research and implementation of variational autoencoders P Sánchez Martín | 1 | 2018 |
| Exploring the Boundaries of Ambient Awareness in Twitter P Sanchez-Martin, S Utz, I Valera arXiv preprint arXiv:2403.17776, 2024 | | 2024 |
| FRUNI and FTREE synthetic knowledge graphs for evaluating explainability PS Martin, T Besold, P Kumari XAI in Action: Past, Present, and Future Applications, 2023 | | 2023 |
| Prediction Tasks in Graphs: a Framework to Control the Interpretability-Performance Trade-off PS Martin, KA Khan, I Valera | | 2023 |
| VARIATIONAL MIXTURE OF HYPERGENERATORS B Koyuncu, P Sánchez-Martín, I Peis, PM Olmos, I Valera arXiv preprint arXiv:2302.06223, 2023 | | 2023 |
Isabel ValeraSaarland University and Max Planck Institute for Software Systems在 cs.uni-saarland.de 的电子邮件经过验证
