Neural Network Visualization

Abstract

We have developed graphics to visualize static and dynamic information in layered neural network learning systems. Emphasis was placed on creating new visuals that make use of spatial arrangements, size information, animation and color. We applied these tools to the study of back-propagation learning of simple Boolean predicates, and have obtained new insights into the dynamics of the learning process.