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Explainable artificial intelligence

XAI refers to methods and techniques in the application of artificial intelligence (AI) such that the results of the solution can be understood by humans. It contrasts with the concept of the "black box" in machine learning where even its designers cannot explain why an AI arrived at a specific decision. XAI may be an implementation of the social right to explanation. XAI is relevant even if there is no legal right or regulatory requirement—for example, XAI can improve the user experience of a product or service by helping end users trust that the AI is making good decisions. This way the aim of XAI is to explain what has been done, what is done right now, what will be done next and unveil the information the actions are based on. These characteristics make it possible (i) to confirm existing knowledge (ii) to challenge existing knowledge and (iii) to generate new assumptions.

Papers

Showing 301350 of 971 papers

TitleStatusHype
Explainable Artificial Intelligence and Multicollinearity : A Mini Review of Current ApproachesCode0
Explainability in Process Outcome Prediction: Guidelines to Obtain Interpretable and Faithful ModelsCode0
Explainable Learning with Gaussian ProcessesCode0
Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate ScienceCode0
Tackling the Accuracy-Interpretability Trade-off in a Hierarchy of Machine Learning Models for the Prediction of Extreme HeatwavesCode0
Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence0
Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation0
Automatic explanation of the classification of Spanish legal judgments in jurisdiction-dependent law categories with tree estimators0
Disproving XAI Myths with Formal Methods -- Initial Results0
Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence0
An Explainable AI Framework for Artificial Intelligence of Medical Things0
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering0
Automated Quality Control of Vacuum Insulated Glazing by Convolutional Neural Network Image Classification0
Disagreement amongst counterfactual explanations: How transparency can be deceptive0
Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If Explorations0
Automated Processing of eXplainable Artificial Intelligence Outputs in Deep Learning Models for Fault Diagnostics of Large Infrastructures0
An Experimentation Platform for Explainable Coalition Situational Understanding0
Directions for Explainable Knowledge-Enabled Systems0
DiCoFlex: Model-agnostic diverse counterfactuals with flexible control0
Automated facial recognition system using deep learning for pain assessment in adults with cerebral palsy0
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning0
Diagnosis of Paratuberculosis in Histopathological Images Based on Explainable Artificial Intelligence and Deep Learning0
Automated Explanation Selection for Scientific Discovery0
Diagnosis of Acute Poisoning Using Explainable Artificial Intelligence0
Developing Guidelines for Functionally-Grounded Evaluation of Explainable Artificial Intelligence using Tabular Data0
Automated detection of motion artifacts in brain MR images using deep learning and explainable artificial intelligence0
Détection d'objets célestes dans des images astronomiques par IA explicable0
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models0
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI)0
Adversarial Attack for Explanation Robustness of Rationalization Models0
Detecting Anomalies in Blockchain Transactions using Machine Learning Classifiers and Explainability Analysis0
Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity0
A User-Centred Framework for Explainable Artificial Intelligence in Human-Robot Interaction0
Designing Explainable Predictive Machine Learning Artifacts: Methodology and Practical Demonstration0
Designing explainable artificial intelligence with active inference: A framework for transparent introspection and decision-making0
A Unified Framework for Evaluating the Effectiveness and Enhancing the Transparency of Explainable AI Methods in Real-World Applications0
A New Deep Learning and XAI-Based Algorithm for Features Selection in Genomics0
Designing ECG Monitoring Healthcare System with Federated Transfer Learning and Explainable AI0
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma0
Augmented cross-selling through explainable AI -- a case from energy retailing0
Advancing Nearest Neighbor Explanation-by-Example with Critical Classification Regions0
Deep Unsupervised Identification of Selected SNPs between Adapted Populations on Pool-seq Data0
Deep Learning Reproducibility and Explainable AI (XAI)0
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing0
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain0
Deep Learning for predicting rate-induced tipping0
A Turing Test for Transparency0
Attributions Beyond Neural Networks: The Linear Program Case0
Deciphering knee osteoarthritis diagnostic features with explainable artificial intelligence: A systematic review0
A Transformer variant for multi-step forecasting of water level and hydrometeorological sensitivity analysis based on explainable artificial intelligence technology0
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