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researcher

Ziwei Zhang

39 papers hereh-index 231.7k citations76 works total

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

author position
  • first author3
  • middle author27
  • last author7

Across the 37 of 39 papers where every author was matched, so the position is known.

fields
  • cs.LG26
  • cs.AI4
  • cs.CL4
  • cs.IR2
  • cs.CR1
  • cs.CV1
same name
  • Ziwei Zhang — 11 papers, h 24
  • Ziwei Zhang — 6 papers, h 4
  • Ziwei Zhang — 5 papers, h 6
  • Ziwei Zhang — 3 papers, h 1
  • Ziwei Zhang — 1 paper, h 3
  • Ziwei Zhang — 1 paper

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 citedOut-Of-Distribution Generalization on Graphs: A Survey

26 citations · 82 across the 35 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022★ 12 cited

NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search

Yijian Qin, Ziwei Zhang, Xin Wang +2

Graph neural architecture search (GraphNAS) has recently aroused considerable attention in both academia and industry. However, two key challenges seriously hinder the further rese…

cs.LG2022

Learning to Solve Travelling Salesman Problem with Hardness-adaptive Curriculum

Zeyang Zhang, Ziwei Zhang, Xin Wang +1

Various neural network models have been proposed to tackle combinatorial optimization problems such as the travelling salesman problem (TSP). Existing learning-based TSP methods ad…

cs.LG2022★ 26 cited

Out-Of-Distribution Generalization on Graphs: A Survey

Haoyang Li, Xin Wang, Ziwei Zhang +1

Graph machine learning has been extensively studied in both academia and industry. Although booming with a vast number of emerging methods and techniques, most of the literature is…

cs.LG2022★ 6 cited

Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions

Xin Wang, Ziwei Zhang, Haoyang Li +1

Graph machine learning has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and tec…

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