| Manipulating sgd with data ordering attacks I Shumailov, Z Shumaylov, D Kazhdan, Y Zhao, N Papernot, MA Erdogdu, ... Advances in Neural Information Processing Systems 34, 18021-18032, 2021 | 127 | 2021 |
| Now You See Me (CME): Concept-based Model Extraction D Kazhdan, B Dimanov, M Jamnik, P Liò, A Weller 29th International Conference on Information and Knowledge Management (CIKM …, 2020 | 99 | 2020 |
| Gcexplainer: Human-in-the-loop concept-based explanations for graph neural networks LC Magister, D Kazhdan, V Singh, P Liò arXiv preprint arXiv:2107.11889, 2021 | 56 | 2021 |
| Towards robust metrics for concept representation evaluation ME Zarlenga, P Barbiero, Z Shams, D Kazhdan, U Bhatt, A Weller, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 11791 …, 2023 | 34 | 2023 |
| MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library D Kazhdan, Z Shams, P Liò 2020 International Joint Conference on Neural Networks (IJCNN), 2020 | 30 | 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 | 28 | 2022 |
| Encoding concepts in graph neural networks LC Magister, P Barbiero, D Kazhdan, F Siciliano, G Ciravegna, F Silvestri, ... arXiv preprint arXiv:2207.13586, 2022 | 23 | 2022 |
| Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches D Kazhdan, B Dimanov, HA Terre, M Jamnik, P Liò, A Weller The Tenth International Conference on Learning Representations (ICLR 2021 …, 2021 | 21 | 2021 |
| MEME: Generating RNN Model Explanations via Model Extraction D Kazhdan, B Dimanov, M Jamnik, P Liò NeurIPS 2020, HAMLETS workshop, 2020 | 18 | 2020 |
| Human-in-the-loop concept-based explanations for graph neural networks LC Magister, D Kazhdan, V Singh, PG Lio arXiv preprint arXiv:2107.11889, 2021 | 13 | 2021 |
| Concept distillation in graph neural networks LC Magister, P Barbiero, D Kazhdan, F Siciliano, G Ciravegna, F Silvestri, ... World Conference on Explainable Artificial Intelligence, 233-255, 2023 | 10 | 2023 |
| Failing conceptually: Concept-based explanations of dataset shift MA Wijaya, D Kazhdan, B Dimanov, M Jamnik arXiv preprint arXiv:2104.08952, 2021 | 10 | 2021 |
| GCI: a (g) raph (c) oncept (i) nterpretation framework D Kazhdan, B Dimanov, LC Magister, P Barbiero, M Jamnik, P Lio arXiv preprint arXiv:2302.04899, 2023 | 7 | 2023 |
| Is disentanglement all you need D Kazhdan, B Dimanov, HA Terre, M Jamnik, P Lio, A Weller Comparing concept-based & disentanglement approaches. CoRR abs/2104.06917, 2021 | 7 | 2021 |
| GCexplainer: human-in-the-loop concept-based explanations for graph neural networks. arXiv LC Magister, D Kazhdan, V Singh, P Liò arXiv preprint arXiv:2107.11889 10, 2021 | 6 | 2021 |
| GCExplainer: human-in-the-loop concept-based explanations for graph neural networks (2021) LC Magister, D Kazhdan, V Singh, P Liò arXiv preprint arXiv:2107.11889, 0 | 6 | |
| Towards robust metrics for concept representation evaluation M Espinosa Zarlenga, P Barbiero, Z Shams, D Kazhdan, U Bhatt, A Weller, ... arXiv e-prints, arXiv: 2301.10367, 2023 | 4 | 2023 |
| On the quality assurance of concept-based representations ME Zarlenga, P Barbiero, Z Shams, D Kazhdan, U Bhatt, M Jamnik | 4 | 2022 |
| Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations S Cardozo, GI Montero, D Kazhdan, B Dimanov, M Wijaya, M Jamnik, ... arXiv preprint arXiv:2211.07650, 2022 | 2 | 2022 |
| Enhancing Interpretability: The Role of Concept-Based Explanations Across Data Types D Kazhdan PQDT-Global, 2023 | | 2023 |
Mateja JamnikProfessor of Artificial Intelligence, University of CambridgeVerified email at cam.ac.uk
