| Interpretable credit application predictions with counterfactual explanations RM Grath, L Costabello, CL Van, P Sweeney, F Kamiab, Z Shen, F Lecue arXiv preprint arXiv:1811.05245, 2018 | 171 | 2018 |
| Knowledge graph embeddings and explainable AI F Bianchi, G Rossiello, L Costabello, M Palmonari, P Minervini arXiv preprint arXiv:2004.14843, 2020 | 141 | 2020 |
| AmpliGraph: a Library for Representation Learning on Knowledge Graphs L Costabello, S Pai, C Le Van, R McGrath, N McCarthy, P Tabacof https://doi.org/10.5281/zenodo 2595043, 2019 | 102 | 2019 |
| Generating interpretable counterfactual explanations by implicit minimisation of epistemic and aleatoric uncertainties L Schut, O Key, R Mc Grath, L Costabello, B Sacaleanu, Y Gal International Conference on Artificial Intelligence and Statistics, 1756-1764, 2021 | 69 | 2021 |
| Regularizing knowledge graph embeddings via equivalence and inversion axioms P Minervini, L Costabello, E Muñoz, V Nováček, PY Vandenbussche Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 68 | 2017 |
| Probability calibration for knowledge graph embedding models P Tabacof, L Costabello arXiv preprint arXiv:1912.10000, 2019 | 66 | 2019 |
| An artificial intelligence-based tool for data analysis and prognosis in cancer patients: results from the clarify study M Torrente, PA Sousa, R Hernández, M Blanco, V Calvo, A Collazo, ... Cancers 14 (16), 4041, 2022 | 57 | 2022 |
| Context-aware access control for rdf graph stores L Costabello, S Villata, F Gandon ECAI 2012, 282-287, 2012 | 57 | 2012 |
| Adversarial attacks on knowledge graph embeddings via instance attribution methods P Bhardwaj, J Kelleher, L Costabello, D O’Sullivan Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 39 | 2021 |
| Linked data access goes mobile: Context-aware authorization for graph stores L Costabello, S Villata, N Delaforge, F Gandon LDOW-5th WWW Workshop on Linked Data on the Web-2012, 2012 | 38 | 2012 |
| Machine learning–assisted recurrence prediction for patients with early-stage non–small-cell lung cancer A Janik, M Torrente, L Costabello, V Calvo, B Walsh, C Camps, ... JCO Clinical Cancer Informatics 7, e2200062, 2023 | 34 | 2023 |
| Poisoning knowledge graph embeddings via relation inference patterns P Bhardwaj, J Kelleher, L Costabello, D O’Sullivan Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 34 | 2021 |
| Learning embeddings from knowledge graphs with numeric edge attributes S Pai, L Costabello arXiv preprint arXiv:2105.08683, 2021 | 33 | 2021 |
| Determining explanations for predicted links in knowledge graphs L Costabello, F LECUE US Patent 10,877,979, 2020 | 33 | 2020 |
| Accurate prediction of kinase-substrate networks using knowledge graphs V Nováček, G McGauran, D Matallanas, A Vallejo Blanco, P Conca, ... PLoS computational biology 16 (12), e1007578, 2020 | 32 | 2020 |
| Robust explanation constraints for neural networks M Wicker, J Heo, L Costabello, A Weller arXiv preprint arXiv:2212.08507, 2022 | 29 | 2022 |
| Examining explainable clinical decision support systems with think aloud protocols SG Anjara, A Janik, A Dunford-Stenger, K Mc Kenzie, A Collazo-Lorduy, ... Plos one 18 (9), e0291443, 2023 | 25 | 2023 |
| Access control for http operations on linked data L Costabello, S Villata, O Rodriguez Rocha, F Gandon Extended Semantic Web Conference, 185-199, 2013 | 25 | 2013 |
| Integrating user-generated content and pervasive communications C Baladrón, J Aguiar, B Carro, A Sánchez-Esguevillas, M Baldauf, ... IEEE Pervasive Computing 7 (4), 58-61, 2008 | 23 | 2008 |
| Data constraints for polyglot data tiers L Costabello, J Umbrich, R Menday, PY Vandenbussche US Patent App. 15/086,497, 2016 | 22 | 2016 |
Vit NovacekFaculty of Informatics, Masaryk University / Masaryk Memorial Cancer InstituteVerified email at fi.muni.cz
