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researcher

Ying Wu

4 papers here

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

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1
  • q-bio.NC1
ORCID 0009-0001-6768-5118
same name
  • Ying Wu — 33 papers, h 53
  • Ying Wu — 19 papers, h 31
  • Ying Wu — 17 papers, h 65
  • Ying Wu — 11 papers, h 5
  • Ying Wu — 5 papers, h 2
  • Ying Wu — 5 papers, 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
20182025
most citedSemi-supervised Transfer Learning for Image Rain Removal

41 citations · 52 across the 4 of their papers we have counts for

collaborators

4 papers

q-bio.NC2025

Place Cells as Multi-Scale Position Embeddings: Random Walk Transition Kernels for Path Planning

Minglu Zhao, Dehong Xu, Deqian Kong +2

The hippocampus supports spatial navigation by encoding cognitive maps through collective place cell activity. We model the place cell population as non-negative spatial embeddings…

cs.LG2024

"Noisier" Noise Contrastive Eestimation is (Almost) Maximum Likelihood

Peiyu Yu, Dinghuai Zhang, Hengzhi He +10

Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing challenge remains: accurately estimating r…

cs.LG2022★ 11 cited

Latent Diffusion Energy-Based Model for Interpretable Text Modeling

Peiyu Yu, Sirui Xie, Xiaojian Ma +6

Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling. Fueled by its flexibility in the formulation and st…

cs.CV2018★ 41 cited

Semi-supervised Transfer Learning for Image Rain Removal

Wei Wei, Deyu Meng, Qian Zhao +2

Single image rain removal is a typical inverse problem in computer vision. The deep learning technique has been verified to be effective for this task and achieved state-of-the-art…

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