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Neural Network Explainable AI Based on Paraconsistent Analysis: An Extension
2021
Electronics
This paper explores the use of paraconsistent analysis for assessing neural networks from an explainable AI perspective. This is an early exploration paper aiming to understand whether paraconsistent analysis can be applied for understanding neural networks and whether it is worth further develop the subject in future research. The answers to these two questions are affirmative. Paraconsistent analysis provides insightful prediction visualisation through a mature formal framework that provides
doi:10.3390/electronics10212660
fatcat:o23uc24ndfhmpm4i7b67o5ggem