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researcher

Hao Wang

4 papers here

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

author position
  • first author2
  • middle author1
  • last author1

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

fields
  • cs.LG3
  • eess.AS1
ORCID 0000-0003-2129-2148
same name
  • Hao Wang — 36 papers
  • Hao Wang — 23 papers, h 101
  • Hao Wang — 12 papers, h 21
  • Hao Wang — 10 papers, h 12
  • Hao Wang — 7 papers
  • Hao Wang — 6 papers

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
20162023
most citedNatural-Parameter Networks: A Class of Probabilistic Neural Networks

38 citations · 42 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2023★ 2 cited

Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning

Yuxiang Wang, Xiao Yan, Chuang Hu +5

For graph self-supervised learning (GSSL), masked autoencoder (MAE) follows the generative paradigm and learns to reconstruct masked graph edges or node features. Contrastive Learn…

cs.LG2023

Self-discipline on multiple channels

Jiutian Zhao, Liang Luo, Hao Wang

Self-distillation relies on its own information to improve the generalization ability of the model and has a bright future. Existing self-distillation methods either require additi…

eess.AS2020★ 2 cited

U-net Based Direct-path Dominance Test for Robust Direction-of-arrival Estimation

Hao Wang, Kai Chen, Jing Lu

It has been noted that the identification of the time-frequency bins dominated by the contribution from the direct propagation of the target speaker can significantly improve the r…

cs.LG2016★ 38 cited

Natural-Parameter Networks: A Class of Probabilistic Neural Networks

Hao Wang, Xingjian Shi, Dit-Yan Yeung

Neural networks (NN) have achieved state-of-the-art performance in various applications. Unfortunately in applications where training data is insufficient, they are often prone to…

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