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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

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Showing 351–375 of 971 papers

TitleStatusHype
Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100—0
Explainable AI through the Learning of Arguments—0
Explainable AI via Learning to Optimize—0
Explainable Analysis of Deep Learning Methods for SAR Image Classification—0
Explainable Anomaly Detection: Counterfactual driven What-If Analysis—0
Classification of Viral Pneumonia X-ray Images with the Aucmedi Framework—0
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models—0
Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development—0
Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review—0
Explainable Artificial Intelligence Architecture for Melanoma Diagnosis Using Indicator Localization and Self-Supervised Learning—0
CNN-based explanation ensembling for dataset, representation and explanations evaluation—0
Explainable Artificial Intelligence Techniques for Accurate Fault Detection and Diagnosis: A Review—0
eXplainable Artificial Intelligence on Medical Images: A Survey—0
Explainable Artificial Intelligence techniques for interpretation of food datasets: a review—0
Explainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific Survey—0
Explainable Artificial Intelligence: a Systematic Review—0
Explainable artificial intelligence toward usable and trustworthy computer-aided early diagnosis of multiple sclerosis from Optical Coherence Tomography—0
Explainable Artificial Intelligence and Causal Inference based ATM Fraud Detection—0
Enhancing Cancer Diagnosis with Explainable & Trustworthy Deep Learning Models—0
Explainable Artificial Intelligence and Cybersecurity: A Systematic Literature Review—0
Explainable Artificial Intelligence and its potential within Industry—0
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction—0
Explainable Artificial Intelligence Based Fault Diagnosis and Insight Harvesting for Steel Plates Manufacturing—0
Explainable Artificial Intelligence driven mask design for self-supervised seismic denoising—0
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI—0
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