# Authors Title Details Date Pdf/Links/Bibtex Keywords
4Raufi B., Finnegan C., Longo L. A Comparative Analysis of SHAP, LIME, ANCHORS, and DICE for Interpreting a Dense Neural Network in Credit Card Fraud Detection eXplainable Artificial Intelligence, The World Conference (xAI-2024) 2024 Explainable Artificial Intelligence • Credit Card Fraud Detection • Interpretability • methods comparison • SHapley Additive exPlanations • Local Interpretable • Model-agnostic Explanation • ANCHORS • Diverse Counterfactual Explanations
10.1007/978-3-031-63803-9_20
3Raufi B., Longo L.Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios BioMedInformatics 2024 model explainability • mental workload • statistical feature selection • Shapley-based feature selection • alpha and theta EEG band ratios • machine learning • Deep-learning
10.3390/biomedinformatics4010048
2Sullivan R.S., Longo L. Optimizing Deep Q-Learning Experience Replay with SHAP Explanations: Exploring Minimum Experience Replay Buffer Sizes in Reinforcement Learning Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium, co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Deep Reinforcement Learning • Experience Replay • SHapley Additive exPlanations • eXplainable Artificial Intelligence • Machine Learning
1O’ Sullivan R., Longo LExplaining Deep Q-Learning Experience Replay with SHapley Additive exPlanations Machine Learning and Knowledge Extraction 2023 Deep Reinforcement Learning • Experience Replay • SHapley Additive exPlanations • eXplainable Artificial Intelligence • Artificial Intelligence
10.3390/make5040072
# Authors Title Details Date Pdf/Links/Bibtex Keywords