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Classification of Explainable Artificial Intelligence Methods through Their Output Formats
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Interpretable Deep Convolutional Neural Networks via Meta-learning
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Transforming Convolutional Neural Network to an Interpretable Classifier
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Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems
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FINGRAMS: Visual Representations of Fuzzy Rule-Based Inference for Expert Analysis of Comprehensibility
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Nonlinear Support Vector Machine Visualization for Risk Factor Analysis Using Nomograms and Localized Radial Basis Function Kernels
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ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
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Seq2seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models
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explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
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Rule Extraction from Training Data Using Neural Network
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Rule extraction from linear support vector machines
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Nomograms for visualizing support vector machines
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Intelligible models for classification and regression
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Trading Interpretability for Accuracy
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Visual exploration of machine learning results using data cube analysis
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Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations
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Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking
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Adversarial Detection with Model Interpretation
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Exact and Consistent Interpretation for Piecewise Linear Neural Networks
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Towards Explanation of DNN-based Prediction with Guided Feature Inversion
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A Survey of Methods for Explaining Black Box Models
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Learning Model-Agnostic Counterfactual Explanations for Tabular Data
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Explainable Multivariate Time Series Classification
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An Interpretable Classification Framework for Information Extraction from Online Healthcare Forums
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A Comparison Study on Rule Extraction from Neural Network Ensembles, Boosted Shallow Trees, and SVMs
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Improving the Interpretability of Classification Rules Discovered by an Ant Colony Algorithm: Extended Results
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Building interpretable fuzzy models for high dimensional data analysis in cancer diagnosis
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Prototype selection for interpretable classification
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On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
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Characterization of Symbolic Rules Embedded in Deep DIMLP Networks: A Challenge to Transparency of Deep Learning
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Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning
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Anchors: High-Precision Model-Agnostic Explanations
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Beyond Sparsity: Tree Regularization of Deep Models for Interpretability
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Interpreting CNN Knowledge via an Explanatory Graph
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Report on the 2019 International Joint Conferences on Artificial Intelligence Explainable Artificial Intelligence Workshop
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Rationalizing Neural Predictions
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A causal framework for explaining the predictions of black-box sequence-to-sequence models
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Visualizing and Understanding Neural Models in NLP
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Harnessing Deep Neural Networks with Logic Rules
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Explaining Recurrent Neural Network Predictions in Sentiment Analysis
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Visualizing and Understanding Recurrent Networks
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Automatic Rule Extraction from Long Short Term Memory Networks
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Unsupervised Neural-Symbolic Integration
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SmoothGrad: removing noise by adding noise
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SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
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Interpretability via Model Extraction
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GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
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Interactive Naming for Explaining Deep Neural Networks: A Formative Study
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Decoding Mental States in Social Cognition: Insights from Explainable Artificial Intelligence on HCP fMRI Data
inferred← citeshttps://doi.org/10.3390/make7040158openalex-snapshot
A Multi-Criteria Decision-Making Approach for the Selection of Explainable AI Methods
inferred← citeshttps://doi.org/10.3390/s22134865openalex-snapshot
Quality Models for Artificial Intelligence Systems: Characteristic-Based Approach, Development and Application
inferred← citeshttps://doi.org/10.3390/s25041083openalex-snapshot
High-Knee-Flexion Posture Recognition Using Multi-Dimensional Dynamic Time Warping on Inertial Sensor Data
inferred← citeshttps://doi.org/10.4018/979-8-3373-3576-6.ch003openalex-snapshot
Explainable AI for Malware and DoS Attack Mitigation in Wireless Communication Environments
inferred← citeshttps://doi.org/10.4018/979-8-3373-6400-1.ch001openalex-snapshot
Demystifying Explainable Artificial Intelligence (XAI) in Healthcare
inferred← citeshttps://doi.org/10.4018/979-8-3693-4439-2.ch012openalex-snapshot
Explainable AI (EXAI) for Smart Healthcare Automation
inferred← citeshttps://doi.org/10.4254/wjh.v17.i11.109494openalex-snapshot
Explainable artificial intelligence and ensemble learning for hepatocellular carcinoma classification: State of the art, performance, and clinical implications
inferred← citeshttps://doi.org/10.52866/ijcsm.2023.04.04.010openalex-snapshot
Driver Drowsy and Yawn System Alert Using Deep Cascade Convolution Neural Network DCCNN
inferred← citeshttps://doi.org/10.55041/ijsrem29433openalex-snapshot
Enhancing Transparency and Interpretability in Toxic Comment Classification: A Study on the Integration of Explainable Artificial Intelligence (XAI) Techniques || Dr. Pallavi Devendra Tawde, Mr. Jadyn Dias
inferred← citeshttps://doi.org/10.56726/irjmets60972openalex-snapshot
User Satisfaction and Trust of AI Explanations in Threat Intelligence Analysis: Implications for Acceptance and Usability
inferred← citeshttps://doi.org/10.5753/ihc.2025.10939openalex-snapshot
Communicating Ethical Considerations in Generative AI Systems
inferred← citeshttps://doi.org/10.5755/j02.eie.36316openalex-snapshot
Applying eXplainable AI Techniques to Interpret Machine Learning Predictive Models for the Analysis of Problematic Internet Use among Adolescents
inferred← citeshttps://doi.org/10.59048/2181-1105.1804openalex-snapshot
REVIEW AND ANALASYS OF EXPLAINABLE ARTIFICIAL INTELLIGENCE APPLICATIONS IN DISTRIBUTED SYSTEMS AND MICROSERVICES
inferred← citeshttps://doi.org/10.59287/pcse.356openalex-snapshot
Rule-based Explainable Artificial Intelligence
inferred← citeshttps://doi.org/10.71112/4mvx1985openalex-snapshot
Machine Learning aplicado en la seguridad informática.
inferred← citeshttps://doi.org/10.7717/peerj-cs.3722openalex-snapshot
Explainable and transferable deep reinforcement learning for adaptive patrol of rail-guided robot system
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