Search Results for author:
Found 2 papers, 0 papers with code
DHOG: Deep Hierarchical Object Grouping
We introduce deep hierarchical object grouping (DHOG) that computes a number of distinct discrete representations of images in a hierarchical order, eventually generating representations that better optimise the mutual information objective.
Ranked #18 on
Image Clustering
on CIFAR-10
(using extra training data)
What Information Does a ResNet Compress?
The information bottleneck principle (Shwartz-Ziv & Tishby, 2017) suggests that SGD-based training of deep neural networks results in optimally compressed hidden layers, from an information theoretic perspective.
