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Liang Zhao

5 papers hereh-index 7340 citations16 works total

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

author position
  • middle author1
  • last author4

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.SI1
same name
  • Liang Zhao — 39 papers, h 21
  • Liang Zhao — 38 papers, h 75
  • Liang Zhao — 22 papers, h 13
  • Liang Zhao — 20 papers, h 27
  • Liang Zhao — 17 papers, h 7
  • Liang Zhao — 16 papers, h 23

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
20212023
most citedTemporal Domain Generalization with Drift-Aware Dynamic Neural Networks

6 citations · 11 across the 5 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2023

Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction

Guangji Bai, Ziyang Yu, Zheng Chai +2

Despite the recent success of Graph Neural Networks (GNNs), it remains challenging to train GNNs on large-scale graphs due to neighbor explosions. As a remedy, distributed computin…

cs.LG2022

Deep Spatial Domain Generalization

Dazhou Yu, Guangji Bai, Yun Li +1

Spatial autocorrelation and spatial heterogeneity widely exist in spatial data, which make the traditional machine learning model perform badly. Spatial domain generalization is a…

cs.LG2022★ 6 cited

Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks

Guangji Bai, Chen Ling, Liang Zhao

Temporal domain generalization is a promising yet extremely challenging area where the goal is to learn models under temporally changing data distributions and generalize to unseen…

cs.LG2021★ 5 cited

Heterogeneous Temporal Graph Neural Network

Yujie Fan, Mingxuan Ju, Chuxu Zhang +2

Graph neural networks (GNNs) have been broadly studied on dynamic graphs for their representation learning, majority of which focus on graphs with homogeneous structures in the spa…

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