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researcher

Yang Sui

Rice University

20 papers hereh-index 131.1k citations34 works total

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

author position
  • first author7
  • middle author12

Across the 19 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG4
  • cs.CL3
  • cs.CR1
  • cs.GR1
  • eess.IV1
affiliations
  • Rice University
same name
  • Yang Sui — 6 papers, h 5
  • Yang Sui — 6 papers, h 1
  • Yang Sui — 5 papers, h 2
  • Yang Sui — 1 paper, h 2

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
20212026
most citedCHIP: CHannel Independence-based Pruning for Compact Neural Networks

25 citations · 48 across the 19 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

eess.SP2023

In-Sensor Radio Frequency Computing for Energy-Efficient Intelligent Radar

Yang Sui, Minning Zhu, Lingyi Huang +2

Radio Frequency Neural Networks (RFNNs) have demonstrated advantages in realizing intelligent applications across various domains. However, as the model size of deep neural network…

eess.IV2023

Corner-to-Center Long-range Context Model for Efficient Learned Image Compression

Yang Sui, Ding Ding, Xiang Pan +4

In the framework of learned image compression, the context model plays a pivotal role in capturing the dependencies among latent representations. To reduce the decoding time result…

cs.CV2023

Reconstruction Distortion of Learned Image Compression with Imperceptible Perturbations

Yang Sui, Zhuohang Li, Ding Ding +4

Learned Image Compression (LIC) has recently become the trending technique for image transmission due to its notable performance. Despite its popularity, the robustness of LIC with…

cs.LG2023★ 15 cited

HALOC: Hardware-Aware Automatic Low-Rank Compression for Compact Neural Networks

Jinqi Xiao, Chengming Zhang, Yu Gong +5

Low-rank compression is an important model compression strategy for obtaining compact neural network models. In general, because the rank values directly determine the model comple…

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