most citedDeep network as memory space: complexity, generalization, disentangled representation and interpretability

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2019★ 1 cited

Deep network as memory space: complexity, generalization, disentangled representation and interpretability

X. Dong, L. Zhou

By bridging deep networks and physics, the programme of geometrization of deep networks was proposed as a framework for the interpretability of deep learning systems. Following thi…

quant-ph2017

Is monogamy of entanglement geometrical?

X. Dong, H. W. Chen, L. Zhou

This work aims to understand the monogamy of quantum entanglement from a geometrical point of view. By regarding quantum entanglement as a geometrical structure on the state space…