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Y. Pan

18 papers hereh-index 14808 citations39 works total

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

author position
  • first author5
  • middle author11

Across the 16 of 18 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.CV4
  • eess.AS4
  • cs.AI1
  • cs.CL1
  • cs.SD1
same name
  • Y. Pan — 224 papers
  • Y. Pan — 176 papers, h 18
  • Y. Pan — 154 papers, h 53
  • Y. Pan — 141 papers, h 4
  • Y. Pan — 101 papers
  • Y. Pan — 73 papers, h 11

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
20182023
most citedTensor Networks Meet Neural Networks: A Survey and Future Perspectives

14 citations · 75 across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

eess.AS2022

LMEC: Learnable Multiplicative Absolute Position Embedding Based Conformer for Speech Recognition

Yuguang Yang, Yu Pan, Jingjing Yin +1

This paper proposes a Learnable Multiplicative absolute position Embedding based Conformer (LMEC). It contains a kernelized linear attention (LA) module called LMLA to solve the ti…

quant-ph2022★ 12 cited

Automatic Depth Optimization for Quantum Approximate Optimization Algorithm

Yu Pan, Yifan Tong, Yi Yang

Quantum Approximate Optimization Algorithm (QAOA) is a hybrid algorithm whose control parameters are classically optimized. In addition to the variational parameters, the right cho…

cs.LG2022★ 1 cited

A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks

Yu Pan, Zeyong Su, Ao Liu +3

Tensorial Convolutional Neural Networks (TCNNs) have attracted much research attention for their power in reducing model parameters or enhancing the generalization ability. However…

cs.CV2022

Semantically Proportional Patchmix for Few-Shot Learning

Jingquan Wang, Jing Xu, Yu Pan +1

Few-shot learning aims to classify unseen classes with only a limited number of labeled data. Recent works have demonstrated that training models with a simple transfer learning st…

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