Pertinent Negatives

Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives

In this paper we propose a novel method that provides contrastive explanations justifying the classification of an input by a black box classifier such as a deep neural network. Given an input we find what should be minimally and sufficiently present (viz. important object pixels in an image) to justify its classification and analogously what should be minimally and necessarily absent (viz. bac...

Interpreting Negatives in Discourse

In recent work, tableau-based model generation calculi have been used as computational models of the reasoning processes involved in utterance interpretation. In this linguistic application of an inference technique that was originally developed for automated theorem proving, natural language understanding is treated as a process of generating Herbrand models for the logical form of an utteranc...

Managing incidental and pertinent

Bug Hunting with False Negatives

Safe data abstractions are widely used for verification purposes. Positive verification results can be transferred to the concrete system. When a property is violated in the abstract system, one still has to check whether a concrete violation exists. However, even when the violation scenario is not reproducible in the concrete system (a false negative), it may still contain information on possi...

Digital Processing of Scanned Negatives

image processing, negatives One source of high quality digital image data is scanned photographic negatives, which can be processed to produce high quality color images. The scanned data must be inverted and processed to adjust for the film and scene characteristics. This report details a proposed approach to processing scanned negatives to produce output color images suitable for viewing on a ...