Bayesian Interpolants as Explanations for Neural Inferences

• URL: http://arxiv.org/abs/2004.04198v1
• Date: Wed, 8 Apr 2020 18:45:06 GMT
• Title: Bayesian Interpolants as Explanations for Neural Inferences
• Authors: Kenneth L. McMillan
• Abstract summary: The notion of Craig interpolant is adapted from logical inference to statistical inference and used to explain inferences made by neural networks. The method produces explanations that are concise, understandable and precise.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The notion of Craig interpolant, used as a form of explanation in automated reasoning, is adapted from logical inference to statistical inference and used to explain inferences made by neural networks. The method produces explanations that are at the same time concise, understandable and precise.

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