Comparing neural models using their perceptual discriminability predictions
Jingyang Zhou, Chanwoo Chun, Ajay Subramanian, Eero P. Simoncelli
The paper introduces a method to compare neural models by measuring their perceptual discriminability using metric tensors, demonstrating its effectiveness with color and autoencoder models.