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Found 3 papers, 1 papers with code
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification
As a result, there is a widespread agreement on the importance of endowing Deep Learning models with explanatory capabilities so that they can themselves provide an answer to why a particular prediction was made.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
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Capabilities, Limitations and Challenges of Style Transfer with CycleGANs: A Study on Automatic Ring Design Generation
This work validates the applicability of CycleGANs on style transfer from an initial sketch to a final render in 2D that represents a 3D design, a step that is paramount in every product design process.
Explaining Credit Risk Scoring through Feature Contribution Alignment with Expert Risk Analysts
We bring light by providing an expert-aligned feature relevance score highlighting the disagreement between a credit risk expert and a model feature attribution explanation in order to better quantify the convergence towards a better human-aligned decision making.
