| Graphframex: Towards systematic evaluation of explainability methods for graph neural networks K Amara, R Ying, Z Zhang, Z Han, Y Shan, U Brandes, S Schemm, ... arXiv preprint arXiv:2206.09677, 2022 | 32 | 2022 |
| ReforesTree: A dataset for estimating tropical forest carbon stock with deep learning and aerial imagery G Reiersen, D Dao, B Lütjens, K Klemmer, K Amara, A Steinegger, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12119 …, 2022 | 17 | 2022 |
| Explaining compound activity predictions with a substructure-aware loss for graph neural networks K Amara, R Rodríguez-Pérez, J Jiménez-Luna Journal of cheminformatics 15 (1), 67, 2023 | 4 | 2023 |
| Nearest neighbor search with compact codes: A decoder perspective K Amara, M Douze, A Sablayrolles, H Jégou Proceedings of the 2022 International Conference on Multimedia Retrieval …, 2022 | 4 | 2022 |
| Generative Explanations for Graph Neural Network: Methods and Evaluations J Chen, K Amara, J Yu, R Ying arXiv preprint arXiv:2311.05764, 2023 | 2 | 2023 |
| SyntaxShap: Syntax-aware Explainability Method for Text Generation K Amara, R Sevastjanova, M El-Assady arXiv preprint arXiv:2402.09259, 2024 | 1 | 2024 |
| Powergraph: A power grid benchmark dataset for graph neural networks K Amara, A Varbella, B Gjorgiev, G Sansavini New Frontiers in Graph Learning (GLFrontiers) Workshop@ NeurIPS 2023, 2023 | 1 | 2023 |
| PowerGraph: A power grid benchmark dataset for graph neural networks A Varbella, K Amara, B Gjorgiev, G Sansavini arXiv preprint arXiv:2402.02827, 2024 | | 2024 |
| GInX-Eval: Towards In-Distribution Evaluation of Graph Neural Network Explanations K Amara, M El-Assady, R Ying arXiv preprint arXiv:2309.16223, 2023 | | 2023 |
| A substructure-aware loss for feature attribution in drug discovery K Amara, R Rodriguez-Perez, JJ Luna | | 2022 |
| VF2 AND GLASGOW: PARALLEL INDUCED SUBGRAPH ISOMORPHISM SOLVERS P Lindenberger, A Unagar, K Amara, CI Hu | | |
| Explaining compound activity predictions with a substructure-aware loss for graph neural networks Supporting information K Amara, R Rodríguez-Pérez, J Jiménez-Luna | | |
