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Eoin M. Kenny
Eoin M. Kenny
Senior Associate AI Researcher at JP Morgan Explainable AI Centre
在 jpmorgan.com 的电子邮件经过验证 - 首页
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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
1882021
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
1622021
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
1282019
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
1102021
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
982019
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
672020
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
422021
Towards interpretable deep reinforcement learning with human-friendly prototypes
EM Kenny, M Tucker, J Shah
The Eleventh International Conference on Learning Representations, 2023
372023
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
222019
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
212021
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
152019
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
92021
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
82020
The Utility of “Even if” semifactual explanation to optimise positive outcomes
E Kenny, W Huang
Advances in Neural Information Processing Systems 36, 2024
72024
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
72021
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
62021
Bayesian case-exclusion and explainable AI (XAI) for sustainable farming
EM Kenny, E Ruelle, A Geoghegan, M Temraz, MT Keane
42021
Advancing Post-Hoc Case-Based Explanation with Feature Highlighting
EM Kenny, E Delaney, MT Keane
The International Joint Conference on Artificial Intelligence, 2023
22023
In Pursuit of Regulatable LLMs
E Kenny, J Shah
NeurIPS 2023 Workshop on Regulatable ML, 2023
22023
Human-guided complexity-controlled abstractions
A Peng, M Tucker, E Kenny, N Zaslavsky, P Agrawal, JA Shah
Advances in Neural Information Processing Systems 36, 2024
12024
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