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Jiao He

4 papers hereh-index 442 citations6 works total

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

author position
  • middle author4

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

fields
  • cs.CV2
  • cs.LG2
same name
  • Jiao He — 13 papers, h 16
  • Jiao He — 8 papers, h 5
  • Jiao He — 4 papers
  • Jiao He — 1 paper, h 10
  • Jiao He — 1 paper, h 2
  • Jiao He — 1 paper

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 citedGOAt: Explaining Graph Neural Networks via Graph Output Attribution

2 citations · 2 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2025

PixelMan: Consistent Object Editing with Diffusion Models via Pixel Manipulation and Generation

Liyao Jiang, Negar Hassanpour, Mohammad Salameh +4

Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving…

cs.LG2024

EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time

Shengyao Lu, Bang Liu, Keith G. Mills +2

Understanding and explaining the predictions of Graph Neural Networks (GNNs), is crucial for enhancing their safety and trustworthiness. Subgraph-level explanations are gaining att…

cs.CV2024

Building Optimal Neural Architectures using Interpretable Knowledge

Keith G. Mills, Fred X. Han, Mohammad Salameh +5

Neural Architecture Search is a costly practice. The fact that a search space can span a vast number of design choices with each architecture evaluation taking nontrivial overhead…

cs.LG2024★ 2 cited

GOAt: Explaining Graph Neural Networks via Graph Output Attribution

Shengyao Lu, Keith G. Mills, Jiao He +2

Understanding the decision-making process of Graph Neural Networks (GNNs) is crucial to their interpretability. Most existing methods for explaining GNNs typically rely on training…

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