xAI (1)

Publications

2023

Ettore Mariotti, Adarsa Sivaprasad, Jose Maria Alonso-Moral
Beyond Prediction Similarity: ShapGAP for Evaluating Faithful Surrogate Models in XAI. xAI (1) (2023)
Lisa Anita De Santi, Filippo Bargagna, Maria Filomena Santarelli, Vincenzo Positano
Evaluating Explanations of an Alzheimer's Disease 18F-FDG Brain PET Black-Box Classifier. xAI (1) (2023)
Maximilian Muschalik, Fabian Fumagalli, Rohit Jagtani, Barbara Hammer, Eyke Hüllermeier
iPDP: On Partial Dependence Plots in Dynamic Modeling Scenarios. xAI (1) (2023)
Jakob Mannmeusel, Mario Rothfelder, Samaneh Khoshrou
Speeding Things Up. Can Explainability Improve Human Learning? xAI (1) (2023)
Maria Carla Calzarossa, Paolo Giudici, Rasha Zieni
Explainable Machine Learning for Bag of Words-Based Phishing Detection. xAI (1) (2023)
Christian A. Scholbeck, Henri Funk, Giuseppe Casalicchio
Algorithm-Agnostic Feature Attributions for Clustering. xAI (1) (2023)
Avleen Malhi, Kary Främling
An Evaluation of Contextual Importance and Utility for Outcome Explanation of Black-Box Predictions for Medical Datasets. xAI (1) (2023)
Dimitry Mindlin, Malte Schilling, Philipp Cimiano
ABC-GAN: Spatially Constrained Counterfactual Generation for Image Classification Explanations. xAI (1) (2023)
Jean Dessain, Nora Bentaleb, Fabien Vinas
Cost of Explainability in AI: An Example with Credit Scoring Models. xAI (1) (2023)
Justus Sagemüller, Olivier Verdier
Ablation Path Saliency. xAI (1) (2023)
Chiara Natali, Lorenzo Famiglini, Andrea Campagner, Giovanni Andrea La Maida, Enrico Gallazzi, Federico Cabitza
Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making. xAI (1) (2023)
Avleen Malhi, Vlad Apopei, Kary Främling
Understanding Unsupervised Learning Explanations Using Contextual Importance and Utility. xAI (1) (2023)
Pedro Sequeira, Melinda T. Gervasio
IxDRL: A Novel Explainable Deep Reinforcement Learning Toolkit Based on Analyses of Interestingness. xAI (1) (2023)
Jingyu Hu, Yizhu Liang, Weiyu Zhao, Kevin McAreavey, Weiru Liu
An Interactive XAI Interface with Application in Healthcare for Non-experts. xAI (1) (2023)
Laura State, Salvatore Ruggieri, Franco Turini
Reason to Explain: Interactive Contrastive Explanations (REASONX). xAI (1) (2023)
Deborah Baum, Kevin Baum, Timo P. Gros, Verena Wolf
XAI Requirements in Smart Production Processes: A Case Study. xAI (1) (2023)
Valentina Ghidini
The Xi Method: Unlocking the Mysteries of Regression with Statistics. xAI (1) (2023)
Timo Freiesleben, Gunnar König
Dear XAI Community, We Need to Talk! - Fundamental Misconceptions in Current XAI Research. xAI (1) (2023)
Francesco Sovrano, Fabio Vitali
Perlocution vs Illocution: How Different Interpretations of the Act of Explaining Impact on the Evaluation of Explanations and XAI. xAI (1) (2023)
Kristin Blesch, Marvin N. Wright, David S. Watson
Unfooling SHAP and SAGE: Knockoff Imputation for Shapley Values. xAI (1) (2023)
Minal Suresh Patil, Kary Främling
Do Intermediate Feature Coalitions Aid Explainability of Black-Box Models? xAI (1) (2023)
Carlo Abrate, Giulia Preti, Francesco Bonchi
Counterfactual Explanations for Graph Classification Through the Lenses of Density. xAI (1) (2023)
Andrea Apicella, Luca Di Lorenzo, Francesco Isgrò, Andrea Pollastro, Roberto Prevete
Strategies to Exploit XAI to Improve Classification Systems. xAI (1) (2023)
Oleksandr Davydko, Vladimir Pavlov, Luca Longo
Selecting Textural Characteristics of Chest X-Rays for Pneumonia Lesions Classification with the Integrated Gradients XAI Attribution Method. xAI (1) (2023)
Deepan Chakravarthi Padmanabhan, Paul G. Plöger, Octavio Arriaga, Matias Valdenegro-Toro
Sanity Checks for Saliency Methods Explaining Object Detectors. xAI (1) (2023)
Kary Främling
Feature Importance versus Feature Influence and What It Signifies for Explainable AI. xAI (1) (2023)
Julian Tritscher, Maximilian Wolf, Andreas Hotho, Daniel Schlör
Evaluating Feature Relevance XAI in Network Intrusion Detection. xAI (1) (2023)
José Luis Corcuera Bárcena, Pietro Ducange, Francesco Marcelloni, Alessandro Renda, Fabrizio Ruffini
Federated Learning of Explainable Artificial Intelligence Models for Predicting Parkinson's Disease Progression. xAI (1) (2023)
Meike Nauta, Christin Seifert
The Co-12 Recipe for Evaluating Interpretable Part-Prototype Image Classifiers. xAI (1) (2023)
Paolo Giudici, Emanuela Raffinetti
Lorenz Zonoids for Trustworthy AI. xAI (1) (2023)
Sarah Holm, Luís Macedo
The Accuracy and Faithfullness of AL-DLIME - Active Learning-Based Deterministic Local Interpretable Model-Agnostic Explanations: A Comparison with LIME and DLIME in Medicine. xAI (1) (2023)
Labhaoise NíFhaoláin, Andrew Hines, Vivek Nallur
Statutory Professions in AI Governance and Their Consequences for Explainable AI. xAI (1) (2023)
Christoph Molnar, Timo Freiesleben, Gunnar König, Julia Herbinger, Tim Reisinger, Giuseppe Casalicchio, Marvin N. Wright, Bernd Bischl
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process. xAI (1) (2023)
Marcel Robeer, Floris Bex, Ad Feelders, Henry Prakken
Explaining Model Behavior with Global Causal Analysis. xAI (1) (2023)
Fatima Ezzeddine, Omran Ayoub, Davide Andreoletti, Silvia Giordano
SAC-FACT: Soft Actor-Critic Reinforcement Learning for Counterfactual Explanations. xAI (1) (2023)
Isacco Beretta, Martina Cinquini
The Importance of Time in Causal Algorithmic Recourse. xAI (1) (2023)

volume 1901, 2023

Explainable Artificial Intelligence - First World Conference, xAI 2023, Lisbon, Portugal, July 26-28, 2023, Proceedings, Part I xAI (1) 1901 (2023)