Eoin M. Kenny
Orcid: 0000-0001-5800-2525
According to our database1,
Eoin M. Kenny
authored at least 20 papers
between 2019 and 2024.
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Bibliography
2024
A Hybrid Model that Combines Machine Learning and Mechanistic Models for Useful Grass Growth Prediction.
Comput. Electron. Agric., 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
2021
Explaining Deep Learning using examples: Optimal feature weighting methods for twin systems using post-hoc, explanation-by-example in XAI.
Knowl. Based Syst., 2021
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation.
CoRR, 2021
Explaining black-box classifiers using <i>post-hoc</i> explanations-by-example: The effect of explanations and error-rates in XAI user studies.
Artif. Intell., 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future.
Proceedings of the Case-Based Reasoning Research and Development, 2021
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
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.
CoRR, 2020
Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
Post-hoc Explanation Options for XAI in Deep Learning: The Insight Centre for Data Analytics Perspective.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification.
Proceedings of the 28th International Conference on Computational Linguistics, 2020
2019
The Twin-System Approach as One Generic Solution for XAI: An Overview of ANN-CBR Twins for Explaining Deep Learning.
CoRR, 2019
How Case Based Reasoning Explained Neural Networks: An XAI Survey of Post-Hoc Explanation-by-Example in ANN-CBR Twins.
CoRR, 2019
Twin-Systems to Explain Artificial Neural Networks using Case-Based Reasoning: Comparative Tests of Feature-Weighting Methods in ANN-CBR Twins for XAI.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI).
Proceedings of the Case-Based Reasoning Research and Development, 2019
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-Systems.
Proceedings of the Case-Based Reasoning Research and Development, 2019