D. H. Smith

Spatial Attention Noise Masking for Causally Sufficient Interpretability

We present a novel causal approach to interpretability for computer vision models that dynamically masks the input image prior to classification. The interpretability of deep learning predictions is critical in high-stakes fields such as medical imaging, security, and autonomous driving. Most interpretability methods a...