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Explainable Artificial Intelligence (XAI)

Explainable Artificial Intelligence

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Showing 801–850 of 1041 papers

TitleStatusHype
nn2poly: An R Package for Converting Neural Networks into Interpretable Polynomials—0
Non-Uniform Interpolation in Integrated Gradients for Low-Latency Explainable-AI—0
OAK4XAI: Model towards Out-Of-Box eXplainable Artificial Intelligence for Digital Agriculture—0
OMENN: One Matrix to Explain Neural Networks—0
On Computing Probabilistic Abductive Explanations—0
On Computing Probabilistic Explanations for Decision Trees—0
On Computing Relevant Features for Explaining NBCs—0
Towards trustable SHAP scores—0
On Evaluating Explainability Algorithms—0
On the Computational Intelligibility of Boolean Classifiers—0
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations—0
On the Effect of Information Asymmetry in Human-AI Teams—0
On the Importance of Domain-specific Explanations in AI-based Cybersecurity Systems (Technical Report)—0
On the Influence of Explainable AI on Automation Bias—0
On the Road to Clarity: Exploring Explainable AI for World Models in a Driver Assistance System—0
On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System—0
On Understanding the Influence of Controllable Factors with a Feature Attribution Algorithm: a Medical Case Study—0
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey—0
OPTDTALS: Approximate Logic Synthesis via Optimal Decision Trees Approach—0
Optimizing Binary Decision Diagrams with MaxSAT for classification—0
Optimizing Explanations by Network Canonization and Hyperparameter Search—0
Overcoming Catastrophic Forgetting by XAI—0
Overlap Number of Balls Model-Agnostic CounterFactuals (ONB-MACF): A Data-Morphology-based Counterfactual Generation Method for Trustworthy Artificial Intelligence—0
Painting the black box white: experimental findings from applying XAI to an ECG reading setting—0
Echoes of Biases: How Stigmatizing Language Affects AI Performance—0
Pitfalls of Explainable ML: An Industry Perspective—0
Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier—0
Polynomial Threshold Functions of Bounded Tree-Width: Some Explainability and Complexity Aspects—0
Post-hoc explanation of black-box classifiers using confident itemsets—0
Precision of Individual Shapley Value Explanations—0
Predicting and explaining nonlinear material response using deep Physically Guided Neural Networks with Internal Variables—0
Predictive K-means with local models—0
Principles of Explanation in Human-AI Systems—0
Privacy Meets Explainability: A Comprehensive Impact Benchmark—0
Privacy-Preserving Federated Learning with Differentially Private Hyperdimensional Computing—0
Privacy Risks and Preservation Methods in Explainable Artificial Intelligence: A Scoping Review—0
Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI—0
Proceedings of the AI-HRI Symposium at AAAI-FSS 2020—0
Process Knowledge-infused Learning for Suicidality Assessment on Social Media—0
Process Knowledge-infused Learning for Clinician-friendly Explanations—0
Propagated Perturbation of Adversarial Attack for well-known CNNs: Empirical Study and its Explanation—0
Explainability of Predictive Process Monitoring Results: Can You See My Data Issues?Code0
From Philosophy to Interfaces: an Explanatory Method and a Tool Inspired by Achinstein's Theory of ExplanationCode0
Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic DatasetCode0
Quantitative Analysis of Primary Attribution Explainable Artificial Intelligence Methods for Remote Sensing Image ClassificationCode0
cito: An R package for training neural networks using torchCode0
Explainability in Practice: Estimating Electrification Rates from Mobile Phone Data in SenegalCode0
An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray ImagesCode0
Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target PredictionCode0
Eliminating The Impossible, Whatever Remains Must Be TrueCode0
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