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Tianfu Wu

North Carolina State University

47 papers hereh-index 323.7k citations128 works total

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

author position
  • first author2
  • middle author25
  • last author17

Across the 44 of 47 papers where every author was matched, so the position is known.

fields
  • cs.CV37
  • cs.LG5
  • eess.SP2
  • cs.RO1
  • eess.IV1
  • stat.ML1
affiliations
  • North Carolina State University
Homepage
same name
  • Tianfu Wu — 4 papers, h 3
  • Tianfu Wu — 4 papers, h 3
  • Tianfu Wu — 3 papers, h 0
  • Tianfu Wu — 3 papers, h 2
  • Tianfu Wu — 2 papers, h 4
  • Tianfu Wu — 2 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
20132023
most citedLearn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting

79 citations · 406 across the 47 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.LG2020★ 2 cited

Local Clustering with Mean Teacher for Semi-supervised Learning

Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra +2

The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable performance on several semi-supervised benchmark datasets. MT maintains a teacher model's weights as the ex…

cs.CV2020★ 1 cited

Holistically-Attracted Wireframe Parsing

Nan Xue, Tianfu Wu, Song Bai +4

This paper presents a fast and parsimonious parsing method to accurately and robustly detect a vectorized wireframe in an input image with a single forward pass. The proposed metho…

cs.CV2020★ 19 cited

Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis

Wei Sun, Tianfu Wu

With the remarkable recent progress on learning deep generative models, it becomes increasingly interesting to develop models for controllable image synthesis from reconfigurable i…

cs.LG2020★ 19 cited

Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Richeng Jin, Yufan Huang, Xiaofan He +2

Federated learning (FL) has emerged as a prominent distributed learning paradigm. FL entails some pressing needs for developing novel parameter estimation approaches with theoretic…

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