| Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI G Warren, MT Keane, RMJ Byrne IJCAI-ECAI’22 Workshop: Cognitive Aspects of Knowledge Representation, 2022 | 27 | 2022 |
| Young and restless, old and focused: Age-differences in mind-wandering frequency and phenomenology. CN Moran, DP McGovern, G Warren, RÓ Grálaigh, JPM Kenney, ... Psychology and aging 36 (2), 252, 2021 | 22 | 2021 |
| Better counterfactuals, ones people can understand: psychologically-plausible case-based counterfactuals using categorical features for eXplainable AI (XAI) G Warren, B Smyth, MT Keane Case-Based Reasoning Research and Development: 30th International Conference …, 2022 | 15 | 2022 |
| Categorical and continuous features in counterfactual explanations of AI systems G Warren, RMJ Byrne, MT Keane Proceedings of the 28th International Conference on Intelligent User …, 2023 | 9 | 2023 |
| Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals G Warren, MT Keane, C Gueret, E Delaney IJCAI-23 Workshop on Explainable Artificial Intelligence (XAI), 2023 | 2 | 2023 |
| Explanation in human thinking J Cassens, L Habenicht, J Blohm, R Wegener, J Korman, S Khemlani, ... Proceedings of the Annual Meeting of the Cognitive Science Society 43 (43), 2021 | 2 | 2021 |
| Counterfactual Explanations for eXplainable AI (XAI) G Warren ICCBR Doctoral Consortium 2022 1613, 0073, 2022 | | 2022 |
Mark T KeaneChair of Computer Science, University College DublinVerified email at ucd.ie
