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researcher

Zhan Gao

University of Pennsylvania

14 papers hereh-index 221.7k citations148 works total

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

author position
  • first author11
  • middle author3

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • eess.SP8
  • cs.LG4
  • cs.CV1
  • hep-ph1
affiliations
  • University of Pennsylvania
same name
  • Zhan Gao — 6 papers, h 3
  • Zhan Gao — 5 papers, h 6
  • Zhan Gao — 5 papers, h 1
  • Zhan Gao — 4 papers, h 2
  • Zhan Gao — 1 paper, h 5
  • Zhan Gao — 1 paper, h 7

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
20192023
most citedStochastic Graph Neural Networks

29 citations · 84 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

hep-ph2022★ 15 cited

Forward Inclusive Jet Productions in pA Collisions

Lei Wang, Lin Chen, Zhan Gao +3

Motivated by recent experimental LHC measurements on the forward inclusive jet productions and based on our previous calculations on forward hadron productions, we calculate single…

eess.SP2022

Learning Stable Graph Neural Networks via Spectral Regularization

Zhan Gao, Elvin Isufi

Stability of graph neural networks (GNNs) characterizes how GNNs react to graph perturbations and provides guarantees for architecture performance in noisy scenarios. This paper de…

cs.CV2022★ 4 cited

Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation

Hegui Zhu, Zhan Gao, Jiayi Wang +2

Traditional fine-grained image classification typically relies on large-scale training samples with annotated ground-truth. However, some sub-categories have few available samples…

eess.SP2022★ 6 cited

Learning Stochastic Graph Neural Networks with Constrained Variance

Zhan Gao, Elvin Isufi

Stochastic graph neural networks (SGNNs) are information processing architectures that learn representations from data over random graphs. SGNNs are trained with respect to the exp…

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