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12/30/2021
Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI
This paper quantifies the quality of heatmap-based eXplainable AI method...
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12/30/2021
Self Reward Design with Fine-grained Interpretability
Transparency and fairness issues in Deep Reinforcement Learning may stem...
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12/30/2021
Two Instances of Interpretable Neural Network for Universal Approximations
This paper proposes two bottom-up interpretable neural network (NN) cons...
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04/04/2021
A Modified Convolutional Network for Auto-encoding based on Pattern Theory Growth Function
This brief paper reports the shortcoming of a variant of convolutional n...
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02/05/2021
Convolutional Neural Network Interpretability with General Pattern Theory
Ongoing efforts to understand deep neural networks (DNN) have provided m...
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09/07/2020
Quantifying Explainability of Saliency Methods in Deep Neural Networks
One way to achieve eXplainable artificial intelligence (XAI) is through ...
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09/05/2020
Generalization on the Enhancement of Layerwise Relevance Interpretability of Deep Neural Network
The practical application of deep neural networks are still limited by t...
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11/19/2019
Enhancing the Extraction of Interpretable Information for Ischemic Stroke Imaging from Deep Neural Networks
When artificial intelligence is used in the medical sector, interpretabi...
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07/17/2019