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Siheng Chen

77 papers hereh-index 4810k citations153 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author11
  • middle author53
  • last author10

Across the 74 of 77 papers where every author was matched, so the position is known.

fields
  • cs.CV40
  • cs.LG11
  • eess.SP7
  • cs.RO3
  • cond-mat.soft2
  • cs.CR2
same name
  • Siheng Chen — 31 papers, h 10
  • Siheng Chen — 17 papers, h 11
  • Siheng Chen — 7 papers, h 4
  • Siheng Chen — 4 papers, h 2
  • Siheng Chen — 3 papers, h 1
  • Siheng Chen — 2 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152023
most citedMultivariate Time Series Forecasting with Dynamic Graph Neural ODEs

182 citations · 683 across the 61 of their papers we have counts for

collaborators
Showing 2020 · eess.SPShow all

4 papers · 2 filters

eess.SP2020

Spatio-Temporal Graph Scattering Transform

Chao Pan, Siheng Chen, Antonio Ortega

Although spatio-temporal graph neural networks have achieved great empirical success in handling multiple correlated time series, they may be impractical in some real-world scenari…

eess.SP2020★ 1 cited

Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks

Takuya Fujihashi, Toshiaki Koike-Akino, Siheng Chen +1

In typical point cloud delivery, a sender uses octree-based digital video compression to send three-dimensional (3D) points and color attributes over band-limited links. However, t…

eess.SP2020

Graph Unrolling Networks: Interpretable Neural Networks for Graph Signal Denoising

Siheng Chen, Yonina C. Eldar, Lingxiao Zhao

We propose an interpretable graph neural network framework to denoise single or multiple noisy graph signals. The proposed graph unrolling networks expand algorithm unrolling to th…

eess.SP2020

Efficient and Stable Graph Scattering Transforms via Pruning

Vassilis N. Ioannidis, Siheng Chen, Georgios B. Giannakis

Graph convolutional networks (GCNs) have well-documented performance in various graph learning tasks, but their analysis is still at its infancy. Graph scattering transforms (GSTs)…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.