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Kacper Sokol
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FACE: Feasible and actionable counterfactual explanations
R Poyiadzi, K Sokol, R Santos-Rodriguez, T De Bie, P Flach
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 344-350, 2020
3562020
Explainability fact sheets: a framework for systematic assessment of explainable approaches
K Sokol, P Flach
Proceedings of the 2020 Conference on Fairness, Accountability, and …, 2020
3122020
One Explanation Does Not Fit All
K Sokol, P Flach
KI-Künstliche Intelligenz, 1-16, 2020
153*2020
Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety
K Sokol, PA Flach
SafeAI 2019: AAAI Workshop on Artificial Intelligence Safety 2301 (urn:nbn …, 2019
992019
Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant.
K Sokol, PA Flach
IJCAI, 5868-5870, 2018
792018
bLIMEy: Surrogate Prediction Explanations Beyond LIME
K Sokol, A Hepburn, R Santos-Rodriguez, P Flach
2019 Workshop on Human-Centric Machine Learning (HCML 2019) at the 33rd …, 2019
402019
Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements.
K Sokol, PA Flach
IJCAI, 5785-5786, 2018
382018
FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency
K Sokol, R Santos-Rodriguez, P Flach
Software Impacts, 100406, 2022
362022
LIMEtree: Consistent and Faithful Surrogate Explanations of Multiple Classes
K Sokol, P Flach
arXiv preprint arXiv:2005.01427, 2020
36*2020
FAT Forensics: A Python toolbox for implementing and deploying fairness, accountability and transparency algorithms in predictive systems
K Sokol, A Hepburn, R Poyiadzi, M Clifford, R Santos-Rodriguez, P Flach
Journal of Open Source Software 5 (49), 1904, 2020
272020
Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals
K Sokol, P Flach
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 10035 …, 2019
232019
Releasing eHealth analytics into the wild: Lessons learnt from the SPHERE project
T Diethe, M Holmes, M Kull, M Perello Nieto, K Sokol, H Song, E Tonkin, ...
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
192018
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence
K Sokol, P Flach
arXiv preprint arXiv:2112.14466, 2021
152021
Interpretable Representations in Explainable AI: From Theory to Practice
K Sokol, P Flach
arXiv preprint arXiv:2008.07007, 2020
9*2020
Fairness, Accountability and Transparency in Artificial Intelligence: A Case Study of Logical Predictive Models
K Sokol
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 541-542, 2019
82019
Towards intelligible and robust surrogate explainers: a decision tree perspective
K Sokol
University of Bristol, 2021
72021
Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication
B Keenan, K Sokol
arXiv preprint arXiv:2302.03460, 2023
62023
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components
K Sokol, A Hepburn, R Santos-Rodriguez, P Flach
Journal of Open Source Education 5 (58), 175, 2022
62022
BayCon: Model-agnostic Bayesian Counterfactual Generator
P Romashov, M Gjoreski, K Sokol, MV Martinez, M Langheinrich
IJCAI, 740-746, 2022
62022
Simply Logical–The First Three Decades
P Flach, K Sokol, J Wielemaker
Prolog: The Next 50 Years, 184-193, 2023
52023
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