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Zida Wu

3 papers here

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

author position
  • first author1
  • middle author2

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

fields
  • cs.CV1
  • cs.GT1
  • eess.IV1

identity via Semantic Scholar / OpenAlex

most citedPopulation-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

eess.IV2025

Z-Stack Scanning can Improve AI Detection of Mitosis: A Case Study of Meningiomas

Hongyan Gu, Ellie Onstott, Wenzhong Yan +5

Z-stack scanning is an emerging whole slide imaging technology that captures multiple focal planes alongside the z-axis of a glass slide. Because z-stacking can offer enhanced dept…

cs.CV2024

Supporting Mitosis Detection AI Training with Inter-Observer Eye-Gaze Consistencies

Hongyan Gu, Zihan Yan, Ayesha Alvi +6

The expansion of artificial intelligence (AI) in pathology tasks has intensified the demand for doctors' annotations in AI development. However, collecting high-quality annotations…

cs.GT2024★ 1 cited

Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning

Zida Wu, Mathieu Lauriere, Samuel Jia Cong Chua +3

Mean Field Games (MFGs) have the ability to handle large-scale multi-agent systems, but learning Nash equilibria in MFGs remains a challenging task. In this paper, we propose a dee…

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