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Three levels at which the user’s cognition can be represented in artificial intelligence

Three levels at which the user’s cognition can be represented in artificial intelligence

Targeting resources efficiently and justifiably by combining causal machine learning and theory

Targeting resources efficiently and justifiably by combining causal machine learning and theory

Explanatory machine learning for justified trust in human-AI collaboration: Experiments on file deletion recommendations

Explanatory machine learning for justified trust in human-AI collaboration: Experiments on file deletion recommendations

Editorial: Explainable, Trustworthy, and Responsible AI for the Financial Service Industry

Editorial: Explainable, Trustworthy, and Responsible AI for the Financial Service Industry

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

Comparing Deep Learning Approaches for Understanding Genotype × Phenotype Interactions in Biomass Sorghum

Leveraging Guided Backpropagation to Select Convolutional Neural Networks for Plant Classification

Leveraging Guided Backpropagation to Select Convolutional Neural Networks for Plant Classification

Credit Risk Modeling Using Transfer Learning and Domain Adaptation

Credit Risk Modeling Using Transfer Learning and Domain Adaptation

EXP-Crowd: A Gamified Crowdsourcing Framework for Explainability

EXP-Crowd: A Gamified Crowdsourcing Framework for Explainability

GANterfactual—Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning

GANterfactual—Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning

Financial Risk Management and Explainable, Trustworthy, Responsible AI

Financial Risk Management and Explainable, Trustworthy, Responsible AI

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