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Explainable Artificial Intelligence (XAI)

Explainable Artificial Intelligence

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TitleStatusHype
Explainable Activity Recognition for Smart Home Systems—0
Evaluating the Correctness of Explainable AI Algorithms for Classification—0
Designer-User Communication for XAI: An epistemological approach to discuss XAI design—0
Abstraction, Validation, and Generalization for Explainable Artificial Intelligence—0
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts—0
XAI Handbook: Towards a Unified Framework for Explainable AI—0
XAI-KG: knowledge graph to support XAI and decision-making in manufacturing—0
Where and When: Space-Time Attention for Audio-Visual Explanations—0
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation—0
Exploiting Explanations for Model Inversion Attacks—0
TrustyAI Explainability ToolkitCode0
Explainable AI For COVID-19 CT Classifiers: An Initial Comparison Study—0
Tracking Peaceful Tractors on Social Media -- XAI-enabled analysis of Red Fort Riots 2021—0
Explainable Artificial Intelligence Reveals Novel Insight into Tumor Microenvironment Conditions Linked with Better Prognosis in Patients with Breast Cancer—0
XAI-N: Sensor-based Robot Navigation using Expert Policies and Decision TreesCode0
A Novel Interaction-based Methodology Towards Explainable AI with Better Understanding of Pneumonia Chest X-ray ImagesCode0
DA-DGCEx: Ensuring Validity of Deep Guided Counterfactual Explanations With Distribution-Aware Autoencoder Loss—0
MEG: Generating Molecular Counterfactual Explanations for Deep Graph NetworksCode1
Towards Human-Understandable Visual Explanations:Imperceptible High-frequency Cues Can Better Be Removed—0
Enabling Machine Learning Algorithms for Credit Scoring -- Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models—0
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer InformationCode0
On the Computational Intelligibility of Boolean Classifiers—0
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML—0
Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future—0
Question-Driven Design Process for Explainable AI User Experiences—0
Towards a Rigorous Evaluation of Explainability for Multivariate Time Series—0
Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing—0
Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey—0
Semantic XAI for contextualized demand forecasting explanations—0
Local Explanations via Necessity and Sufficiency: Unifying Theory and PracticeCode0
Explaining the Road Not Taken—0
Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target PredictionCode0
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals—0
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark DatasetCode1
A Comparative Approach to Explainable Artificial Intelligence Methods in Application to High-Dimensional Electronic Health Records: Examining the Usability of XAI—0
Explainable AI in Credit Risk Management—0
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques—0
Shapley values for feature selection: The good, the bad, and the axioms—0
Ada-SISE: Adaptive Semantic Input Sampling for Efficient Explanation of Convolutional Neural Networks—0
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research—0
VitrAI -- Applying Explainable AI in the Real World—0
The human-AI relationship in decision-making: AI explanation to support people on justifying their decisions—0
Principles of Explanation in Human-AI Systems—0
Enhancing Human-Machine Teaming for Medical Prognosis Through Neural Ordinary Differential Equations (NODEs)—0
Mitigating belief projection in explainable artificial intelligence via Bayesian TeachingCode0
Convolutional Neural Network Interpretability with General Pattern Theory—0
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond—0
A Survey on Understanding, Visualizations, and Explanation of Deep Neural Networks—0
Hierarchical Variational Autoencoder for Visual Counterfactuals—0
Matching Representations of Explainable Artificial Intelligence and Eye Gaze for Human-Machine Interaction—0
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