Artificial Intelligence

Papers
(The H4-Index of Artificial Intelligence is 29. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-09-01 to 2024-09-01.)
ArticleCitations
Multiple object tracking: A literature review402
Explaining individual predictions when features are dependent: More accurate approximations to Shapley values254
What do we want from Explainable Artificial Intelligence (XAI)? – A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research251
A survey of inverse reinforcement learning: Challenges, methods and progress234
Reward is enough221
Evaluating XAI: A comparison of rule-based and example-based explanations172
Knowledge graphs as tools for explainable machine learning: A survey119
Explaining black-box classifiers using post-hoc explanations-by-example: The effect of explanations and error-rates in XAI user studies114
Explanation in AI and law: Past, present and future76
Relation between prognostics predictor evaluation metrics and local interpretability SHAP values69
Using ontologies to enhance human understandability of global post-hoc explanations of black-box models68
Logic Tensor Networks66
GLocalX - From Local to Global Explanations of Black Box AI Models65
Levels of explainable artificial intelligence for human-aligned conversational explanations59
Toward personalized XAI: A case study in intelligent tutoring systems58
Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations57
A review of possible effects of cognitive biases on interpretation of rule-based machine learning models54
Evaluating local explanation methods on ground truth49
Swarm intelligence for self-organized clustering47
Analyzing Differentiable Fuzzy Logic Operators46
Multi-view graph convolutional networks with attention mechanism38
Multi-agent pathfinding with continuous time38
Enhanced aspect-based sentiment analysis models with progressive self-supervised attention learning36
Sensitive loss: Improving accuracy and fairness of face representations with discrimination-aware deep learning35
Neural probabilistic logic programming in DeepProbLog33
Assessing the communication gap between AI models and healthcare professionals: Explainability, utility and trust in AI-driven clinical decision-making32
Pairwise symmetry reasoning for multi-agent path finding search31
Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare30
Counterfactual state explanations for reinforcement learning agents via generative deep learning29
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