375 citations · 394 across the 5 of their papers we have counts for
5 papers
Explainable, Stable, and Scalable Graph Convolutional Networks for Learning Graph Representation
Ping-En Lu, Cheng-Shang Chang
The network embedding problem that maps nodes in a graph to vectors in Euclidean space can be very useful for addressing several important tasks on a graph. Recently, graph neural…
A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons
Yi-Cheng Chen, Ping-En Lu, Cheng-Shang Chang +1
In this paper, we conduct mathematical and numerical analyses to address the following crucial questions for COVID-19: (Q1) Is it possible to contain COVID-19? (Q2) When will be th…
A Reinforcement Learning Approach for the Multichannel Rendezvous Problem
Jen-Hung Wang, Ping-En Lu, Cheng-Shang Chang +1
In this paper, we consider the multichannel rendezvous problem in cognitive radio networks (CRNs) where the probability that two users hopping on the same channel have a successful…
Generalized Modularity Embedding: a General Framework for Network Embedding
Cheng-Shang Chang, Ching-Chu Huang, Chia-Tai Chang +2
The network embedding problem aims to map nodes that are similar to each other to vectors in a Euclidean space that are close to each other. Like centrality analysis (ranking) and…
Percolation Threshold for Competitive Influence in Random Networks
Yu-Hsien Peng, Ping-En Lu, Cheng-Shang Chang +1
In this paper, we propose a new averaging model for modeling the competitive influence of candidates among voters in an election process. For such an influence propagation…