| CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks A Lucic, M ter Hoeve, G Tolomei, M de Rijke, F Silvestri AISTATS 2022, 2022 | 195 | 2022 |
| FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles A Lucic, H Oosterhuis, H Haned, M de Rijke AAAI 2022, 2022 | 95 | 2022 |
| Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting A Lucic, H Haned, M de Rijke FAccT 2020, 2020 | 76 | 2020 |
| FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval A Olteanu, J Garcia-Gathright, M de Rijke, MD Ekstrand, A Roegiest, ... ACM SIGIR Forum 53 (2), 20-43, 2021 | 58* | 2021 |
| Aurora: A foundation model for the Earth system C Bodnar, WP Bruinsma, A Lucic, M Stanley, A Vaughan, J Brandstetter, ... arXiv preprint arXiv:2405.13063, 2024 | 55* | 2024 |
| Order in the Court: Explainable AI Methods Prone to Disagreement M Neely, SF Schouten, MJR Bleeker, A Lucic ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend …, 2021 | 44 | 2021 |
| A Song of (Dis) agreement: Evaluating the Evaluation of Explainable Artificial Intelligence in Natural Language Processing M Neely, SF Schouten, M Bleeker, A Lucic HHAI 2022, 2022 | 26 | 2022 |
| Reproducibility as a Mechanism for Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence A Lucic, M Bleeker, S Jullien, S Bhargav, M de Rijke AAAI 2022 (EAAI), 2022 | 26* | 2022 |
| To Trust or Not to Trust a Regressor: Estimating and Explaining Trustworthiness of Regression Predictions K de Bie, A Lucic, H Haned ICML 2021 Workshop on Human in the Loop Learning, 2021 | 14 | 2021 |
| Towards Reproducible Machine Learning Research in Natural Language Processing A Lucic, M Bleeker, S Bhargav, J Forde, K Sinha, J Dodge, S Luccioni, ... ACL 2022 Tutorial Abstracts, 7-11, 2022 | 12 | 2022 |
| Clifford-steerable convolutional neural networks M Zhdanov, D Ruhe, M Weiler, A Lucic, J Brandstetter, P Forré ICML 2022, 2024 | 10 | 2024 |
| A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms A Lucic, M Srikumar, U Bhatt, A Xiang, A Taly, QV Liao, M de Rijke CHI 2021 Workshop on Operationalizing Human-Centred Perspectives in …, 2021 | 10 | 2021 |
| Contrastive Explanations for Large Errors in Retail Forecasting Predictions through Monte Carlo Simulations A Lucic, H Haned, M de Rijke IJCAI 2019 Workshop on Explainable Artificial Intelligence, 2019 | 7 | 2019 |
| Towards Reproducible Machine Learning Research in Information Retrieval A Lucic, M Bleeker, M de Rijke, K Sinha, S Jullien, R Stojnic SIGIR 2022 Tutorial Abstracts, 2022 | 4 | 2022 |
| Explaining Predictions from Tree-based Boosting Ensembles A Lucic, H Haned, M de Rijke SIGIR 2019 Workshop on Fairness, Accountability, Confidentiality …, 2019 | 4 | 2019 |
| Towards the Use of Saliency Maps for Explaining Low-Quality Electrocardiograms to End Users A Lucic, S Ahmad, AF Brinhosa, QV Liao, H Agrawal, U Bhatt, ... ICML 2022 Workshop on Interpretable ML in Healthcare, 2022 | 3 | 2022 |
| XAI Toolsheet: Towards A Documentation Framework for XAI Tools S Karunagaran, A Lucic, C Custis IJCAI 2022 Workshop on XAI, 2022 | 2 | 2022 |
| Explaining Predictions from Machine Learning Models: Algorithms, Users, and Pedagogy A Lucic University of Amsterdam, PhD Thesis, 2022 | | 2022 |
Maarten de RijkeUniversity of Amsterdam & ICAIایمیل تأیید شده در uva.nl