| Explaining black-box classifiers using post-hoc explanations-by-example: The effect of explanations and error-rates in XAI user studies EM Kenny, C Ford, M Quinn, MT Keane Artificial Intelligence 294, 103459, 2021 | 246 | 2021 |
| If only we had better counterfactual explanations: Five key deficits to rectify in the evaluation of counterfactual xai techniques MT Keane, EM Kenny, E Delaney, B Smyth arXiv preprint arXiv:2103.01035, 2021 | 199 | 2021 |
| How Case-Based Reasoning Explains Neural Networks: A Theoretical Analysis of XAI Using Post-Hoc Explanation-by-Example from a Survey of ANN-CBR Twin … MT Keane, EM Kenny Case-Based Reasoning Research and Development: 27th International Conference …, 2019 | 144 | 2019 |
| On generating plausible counterfactual and semi-factual explanations for deep learning EM Kenny, MT Keane Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11575 …, 2021 | 133 | 2021 |
| Twin-systems to explain artificial neural networks using case-based reasoning: Comparative tests of feature-weighting methods in ANN-CBR twins for XAI EM Kenny, MT Keane Kraus, S.(ed.). Proceedings of the Twenty-Eighth International Joint …, 2019 | 105 | 2019 |
| Generating plausible counterfactual explanations for deep transformers in financial text classification L Yang, EM Kenny, TLJ Ng, Y Yang, B Smyth, R Dong arXiv preprint arXiv:2010.12512, 2020 | 82 | 2020 |
| Towards interpretable deep reinforcement learning with human-friendly prototypes EM Kenny, M Tucker, J Shah The Eleventh International Conference on Learning Representations, 2023 | 55 | 2023 |
| Explaining Deep Learning using examples: Optimal feature weighting methods for twin systems using post-hoc, explanation-by-example in XAI EM Kenny, MT Keane Knowledge-Based Systems 233, 107530, 2021 | 53 | 2021 |
| Post-hoc Explanation Options for XAI in Deep Learning: The Insight Centre for Data Analytics Perspective EM Kenny, ED Delaney, D Greene, MT Keane Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 31 | 2021 |
| Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI) EM Kenny, E Ruelle, A Geoghegan, L Shalloo, M O’Leary, M O’Donovan, ... Case-Based Reasoning Research and Development: 27th International Conference …, 2019 | 23 | 2019 |
| The utility of “even if” semifactual explanation to optimise positive outcomes E Kenny, W Huang Advances in Neural Information Processing Systems 36, 52907-52935, 2023 | 18 | 2023 |
| The twin-system approach as one generic solution for XAI: An overview of ANN-CBR twins for explaining deep learning MT Keane, EM Kenny arXiv preprint arXiv:1905.08069, 2019 | 15 | 2019 |
| Handling climate change using counterfactuals: Using counterfactuals in data augmentation to predict crop growth in an uncertain climate future M Temraz, EM Kenny, E Ruelle, L Shalloo, B Smyth, MT Keane Case-Based Reasoning Research and Development: 29th International Conference …, 2021 | 12 | 2021 |
| Bayesian case-exclusion and personalized explanations for sustainable dairy farming EM Kenny, E Ruelle, A Geoghegan, L Shalloo, M O'Leary, M O'Donovan, ... Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 9 | 2021 |
| Play MNIST for me! User studies on the effects of post-hoc, example-based explanations & error rates on debugging a deep learning, black-box classifier C Ford, EM Kenny, MT Keane arXiv preprint arXiv:2009.06349, 2020 | 9 | 2020 |
| Twin systems for deepcbr: A menagerie of deep learning and case-based reasoning pairings for explanation and data augmentation MT Keane, EM Kenny, M Temraz, D Greene, B Smyth arXiv preprint arXiv:2104.14461, 2021 | 8 | 2021 |
| Advancing Post-Hoc Case-Based Explanation with Feature Highlighting EM Kenny, E Delaney, MT Keane The International Joint Conference on Artificial Intelligence, 2023 | 6 | 2023 |
| In pursuit of regulatable llms E Kenny, J Shah NeurIPS 2023 Workshop on Regulatable ML, 2023 | 5 | 2023 |
| Bayesian case-exclusion and explainable AI (XAI) for sustainable farming EM Kenny, E Ruelle, A Geoghegan, M Temraz, MT Keane | 4 | 2021 |
| A Hybrid Model that Combines Machine Learning and Mechanistic Models for Useful Grass Growth Prediction EM Kenny, E Ruelle, MT Keane, L Shalloo Computers and Electronics in Agriculture 219, 108805, 2024 | 3 | 2024 |
Mark T KeaneChair of Computer Science, University College DublinVerified email at ucd.ie
