activity
20152021
most citedEdge of chaos as a guiding principle for modern neural network training

4 citations · 7 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG20214 cited

Edge of chaos as a guiding principle for modern neural network training

Lin Zhang, Ling Feng, Kan Chen +1

The success of deep neural networks in real-world problems has prompted many attempts to explain their training dynamics and generalization performance, but more guiding principles…

physics.soc-ph2021

Identify Hidden Spreaders of Pandemic over Contact Tracing Networks

Shuhong Huang, Jiachen Sun, Ling Feng +3

The COVID-19 infection cases have surged globally, causing devastations to both the society and economy. A key factor contributing to the sustained spreading is the presence of a l…

physics.soc-ph20202 cited

Induced Percolation on Networked Systems

Jiarong Xie, Xiangrong Wang, Ling Feng +3

Percolation theory has been widely used to study phase transitions in complex networked systems. It has also successfully explained several macroscopic phenomena across different f…

cs.LG2019

Optimal Machine Intelligence at the Edge of Chaos

Ling Feng, Lin Zhang, Choy Heng Lai

It has long been suggested that the biological brain operates at some critical point between two different phases, possibly order and chaos. Despite many indirect empirical evidenc…

physics.soc-ph20151 cited

A Simplified Self-Consistent Probabilities Framework to Characterize Percolation Phenomena on Interdependent Networks : An Overview

Ling Feng, Christopher Pineda Monterola, Yanqing Hu

Interdependent networks are ubiquitous in our society, ranging from infrastructure to economics, and the study of their cascading behaviors using percolation theory has attracted m…