Dynamically Typed

Distill: High-Low Frequency Detectors

Ludwig Schubert, Chelsea Voss and Chris Olah published a new entry to the Distill Circuits thread, in which they model connections in trained convolutional neural networks as logical circuits to figure out how they work; I covered what makes this research so interesting last April in Distill: Early Vision in CNNs. Using feature visualization, dataset examples, and synthetic tuning curves, this new article goes in-depth on a relatively unintuitive class of neurons: High-Low Frequency Detectors, which activate when they encounter “directional transitions from low to high spatial frequency.” In one very cool section of the article, the authors combine clusters of high- and low-frequency circuit components into two generic HF- and LF-factors, and show that they play the same roles in the implementation of high-low frequency detectors as their individual components do. As always, the article is a great weekend long read.