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researcher

Fei Wang

4 papers here

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

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.AR1
  • cs.LG1
  • physics.optics1
ORCID 0000-0003-1482-2235
same name
  • Fei Wang — 70 papers, h 137
  • Fei Wang — 25 papers
  • Fei Wang — 20 papers, h 50
  • Fei Wang — 18 papers, h 19
  • Fei Wang — 13 papers, h 16
  • Fei Wang — 7 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

most citedNon-Overlapping Placement of Macro Cells based on Reinforcement Learning in Chip Design

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

collaborators

4 papers

cs.AI2024

Rethink Deep Learning with Invariance in Data Representation

Shuren Qi, Fei Wang, Tieyong Zeng +1

Integrating invariance into data representations is a principled design in intelligent systems and web applications. Representations play a fundamental role, where systems and appl…

cs.LG2024

CCS: Continuous Learning for Customized Incremental Wireless Sensing Services

Qunhang Fu, Fei Wang, Mengdie Zhu +3

Wireless sensing has made significant progress in tasks ranging from action recognition, vital sign estimation, pose estimation, etc. After over a decade of work, wireless sensing…

cs.AR2024★ 3 cited

Non-Overlapping Placement of Macro Cells based on Reinforcement Learning in Chip Design

Tao Yu, Peng Gao, Fei Wang +1

Due to the increasing complexity of chip design, existing placement methods still have many shortcomings in dealing with macro cells coverage and optimization efficiency. Aiming at…

physics.optics2023★ 1 cited

Robust Super-Resolution Imaging Based on a Ring Core Fiber with Orbital Angular Momentum

Zheyu Wu, Ran Gao, Sitong Zhou +8

Single fiber imaging technology offers unique insights for research and inspection in difficult to reach and narrow spaces. In particular, ultra-compact multimode fiber (MMF) imagi…

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