375 citations · 532 across the 28 of their papers we have counts for
6 papers · 1 filter
Positively Correlated Samples Save Pooled Testing Costs
Yi-Jheng Lin, Che-Hao Yu, Tzu-Hsuan Liu +2
The group testing approach that achieves significant cost reduction over the individual testing approach has received a lot of interest lately for massive testing of COVID-19. Many…
Constructions and Comparisons of Pooling Matrices for Pooled Testing of COVID-19
Yi-Jheng Lin, Che-Hao Yu, Tzu-Hsuan Liu +2
In comparison with individual testing, group testing (also known as pooled testing) is more efficient in reducing the number of tests and potentially leading to tremendous cost red…
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…
ALOHA Receivers: a Network Calculus Approach for Analyzing Coded Multiple Access with SIC
Tzu-Hsuan Liu, Che-Hao Yu, Yi-Jheng Lin +2
Motivated by the need to hide the complexity of the physical layer from performance analysis in a layer 2 protocol, a class of abstract receivers, called Poisson receivers, was rec…
Poisson Receivers: a Probabilistic Framework for Analyzing Coded Random Access
Che-Hao Yu, Lin Huang, Cheng-Shang Chang +1
In this paper, we develop a probabilistic framework for analyzing coded random access. Our framework is based on a new abstract receiver (decoder), called a Poisson receiver, that…
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…