John Shi

Orcid: 0000-0003-1607-5018

According to our database1, John Shi authored at least 14 papers between 2001 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2023
Extending DSP to Graph Signal Processing: The Companion Approach.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

Graph Classification via Simple Graph Based Features.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
Graph Signal Processing: Dualizing GSP Sampling in the Vertex and Spectral Domains.
IEEE Trans. Signal Process., 2022

From DSP to GSP: Sampling in Both Domains.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
Using Sparse Spectral Shifts in Graph CNNs.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology.
IEEE Signal Process. Mag., 2020

A Dual Approach to Graph CNNs.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Edge Entropy as an Indicator of the Effectiveness of GNNs over CNNs for Node Classification.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Topics in Graph Signal Processing: Convolution and Modulation.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Pooling in Graph Convolutional Neural Networks.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
On Graph Convolution for Graph CNNs.
Proceedings of the 2018 IEEE Data Science Workshop, 2018

Classification with Vertex-Based Graph Convolutional Neural Networks.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2003
Modeling of Supercritical Fluid Extraction by Neural Networks.
Intell. Autom. Soft Comput., 2003

2001
Modeling of supercritical fluid extraction by artificial neural networks.
Proceedings of the IEEE International Conference on Systems, 2001


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