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Zelin Zang

38 papers hereh-index 14550 citations69 works total

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

author position
  • first author11
  • middle author22
  • last author1

Across the 34 of 38 papers where every author was matched, so the position is known.

fields
  • cs.LG22
  • cs.CV7
  • cs.AI2
  • q-bio.GN2
  • q-bio.PE2
  • cs.CE1
same name
  • Zelin Zang — 7 papers, h 1
  • Zelin Zang — 1 paper, h 3
  • Zelin Zang — 1 paper, h 1
  • Zelin Zang — 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
20202026
most citedArchitecture-Agnostic Masked Image Modeling -- From ViT back to CNN

16 citations · 66 across the 38 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.LG2021

GenURL: A General Framework for Unsupervised Representation Learning

Siyuan Li, Zicheng Liu, Zelin Zang +3

Unsupervised representation learning (URL), which learns compact embeddings of high-dimensional data without supervision, has made remarkable progress recently. However, the develo…

cs.AI2021★ 14 cited

Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks

Zihan Liu, Yun Luo, Zelin Zang +1

Gray-box graph attacks aim at disrupting the performance of the victim model by using inconspicuous attacks with limited knowledge of the victim model. The parameters of the victim…

cs.CV2021★ 1 cited

Exploring Localization for Self-supervised Fine-grained Contrastive Learning

Di Wu, Siyuan Li, Zelin Zang +1

Self-supervised contrastive learning has demonstrated great potential in learning visual representations. Despite their success in various downstream tasks such as image classifica…

cs.LG2021★ 5 cited

Unsupervised Deep Manifold Attributed Graph Embedding

Zelin Zang, Siyuan Li, Di Wu +3

Unsupervised attributed graph representation learning is challenging since both structural and feature information are required to be represented in the latent space. Existing meth…

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