| Neural Bipartite Matching D Georgiev, P Lió Graph Representation Learning & Beyond (ICML workshop), 2020 | 21 | 2020 |
| Algorithmic Concept-based Explainable Reasoning D Georgiev, P Barbiero, D Kazhdan, P Veličković, P Liò Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6685-6693, 2022 | 13 | 2022 |
| HEAT: Hyperedge Attention Networks D Georgiev, M Brockschmidt, M Allamanis Transactions on Machine Learning Research 2022 (2835-8856), https …, 2022 | 12 | 2022 |
| Hypergraph factorization for multi-tissue gene expression imputation R Viñas, CK Joshi, D Georgiev, P Lin, B Dumitrascu, ER Gamazon, P Liò Nature Machine Intelligence, 1-15, 2023 | 9 | 2023 |
| Global concept-based interpretability for graph neural networks via neuron analysis H Xuanyuan, P Barbiero, D Georgiev, LC Magister, P Lió Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10675 …, 2023 | 8 | 2023 |
| PyTorch, Explain! A Python library for Logic Explained Networks P Barbiero, G Ciravegna, D Georgiev, F Giannini arXiv preprint arXiv:2105.11697, 2021 | 8 | 2021 |
| Neural Algorithmic Reasoning for Combinatorial Optimisation D Georgiev, D Numeroso, D Bacciu, P Liò The Second Learning on Graphs Conference, 2023 | 5 | 2023 |
| Parallel Algorithms Align with Neural Execution V Engelmayer, D Georgiev, P Veličković The Second Learning on Graphs Conference, 2023 | 4 | 2023 |
| Beyond Erdos-Renyi: Generalization in Algorithmic Reasoning on Graphs DG Georgiev, P Lio, J Bachurski, J Chen, T Shi, L Giusti The Second Learning on Graphs Conference, 2023 | 2 | 2023 |
| LENs: a Python library for Logic Explained Networks. P Barbiero, G Ciravegna, D Georgiev, F Giannini CoRR, 2021 | 1 | 2021 |
| The Deep Equilibrium Algorithmic Reasoner D Georgiev, P Liò, D Buffelli arXiv preprint arXiv:2402.06445, 2024 | | 2024 |
| NARTI: Neural Algorithmic Reasoning for Trajectory Inference D Georgiev, R Vinas, S Considine, B Dumitrascu, P Lio The 2023 ICML Workshop on Computational Biology., 2023 | | 2023 |
