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Gan Sun

38 papers hereh-index 344.3k citations182 works total

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

author position
  • first author5
  • middle author15
  • last author2

Across the 22 of 38 papers where every author was matched, so the position is known.

fields
  • hep-ex15
  • cs.CV12
  • cs.LG7
  • cond-mat.mtrl-sci1
  • cond-mat.supr-con1
  • cs.CR1
same name
  • Gan Sun — 4 papers, h 3
  • Gan Sun — 3 papers, h 4
  • Gan Sun — 1 paper, h 1
  • Gan Sun — 1 paper, h 1
  • Gan Sun — 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
20172023
most citedScanning tunneling microscopy and spectroscopy of twisted trilayer graphene

41 citations · 197 across the 37 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.LG2019

Lifelong Spectral Clustering

Gan Sun, Yang Cong, Qianqian Wang +2

In the past decades, spectral clustering (SC) has become one of the most effective clustering algorithms. However, most previous studies focus on spectral clustering tasks with a f…

cs.LG2019

Visual Tactile Fusion Object Clustering

Tao Zhang, Yang Cong, Gan Sun +2

Object clustering, aiming at grouping similar objects into one cluster with an unsupervised strategy, has been extensivelystudied among various data-driven applications. However, m…

cs.CV2019★ 9 cited

Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation

Jiahua Dong, Yang Cong, Gan Sun +1

Weakly-supervised learning under image-level labels supervision has been widely applied to semantic segmentation of medical lesions regions. However, 1) most existing models rely o…

cs.LG2019★ 6 cited

Representative Task Self-selection for Flexible Clustered Lifelong Learning

Gan Sun, Yang Cong, Qianqian Wang +2

Consider the lifelong machine learning paradigm whose objective is to learn a sequence of tasks depending on previous experiences, e.g., knowledge library or deep network weights.…

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