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Explaining neural network predictions of material strength
It is common in computer vision to employ an explainable AI saliency map to tell one what parts of an image are important to the network's decision.
Reliable Graph Neural Network Explanations Through Adversarial Training
Graph neural network (GNN) explanations have largely been facilitated through post-hoc introspection.
Generative Counterfactual Introspection for Explainable Deep Learning
In this work, we propose an introspection technique for deep neural networks that relies on a generative model to instigate salient editing of the input image for model interpretation.
Preprint ARPPS Augmented Reality Pipeline Prospect System
This is the preprint version of our paper on ICONIP.
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