1 citations · 2 across the 19 of their papers we have counts for
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Causal Explanations for Image Classifiers
Hana Chockler, David A. Kelly, Daniel Kroening +1
Existing algorithms for explaining the output of image classifiers use different definitions of explanations and a variety of techniques to find them. However, none of the existing…
Real-Time Incremental Explanations for Object Detectors in Autonomous Driving
Santiago Calderón-Peña, Hana Chockler, David A. Kelly
Object detectors are widely used in safety-critical real-time applications such as autonomous driving. Explainability is especially important for safety-critical applications, and…
It's a Feature, Not a Bug: Measuring Creative Fluidity in Image Generators
Aditi Ramaswamy, Melane Navaratnarajah, Hana Chockler
With the rise of freely available image generators, AI-generated art has become the centre of a series of heated debates, one of which concerns the concept of human creativity. Can…
Explaining Image Classifiers
Hana Chockler, Joseph Y. Halpern
We focus on explaining image classifiers, taking the work of Mothilal et al. [2021] (MMTS) as our point of departure. We observe that, although MMTS claim to be using the definitio…