Google & DeepMind Propose Geometric Complexity for DNN Analysis and Evaluation

In the new paper Why Neural Networks Find Simple Solutions: The Many Regularizers of Geometric Complexity, a research team from Google and DeepMind proposes Geometric Complexity (GC), a measure of deep neural network model complexity that serves as a useful tool for understanding the underlying mechanisms of complexity control.

ai analysis artificial intelligence complexity deepmind deep-neural-networks dnn evaluation geometric complexity google machine learning machine learning & data science ml regularization research technology