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researcher

Rui She

4 papers here

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.LG2
  • cs.CV1
  • cs.IT1
ORCID 0000-0002-5211-1664
same name
  • Rui She — 14 papers, h 10
  • Rui She — 2 papers, h 3
  • Rui She — 1 paper, h 1

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 citedHypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic Fusion

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

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2024

Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study

Qiyu Kang, Kai Zhao, Yang Song +5

In this work, we rigorously investigate the robustness of graph neural fractional-order differential equation (FDE) models. This framework extends beyond traditional graph neural (…

cs.LG2023★ 9 cited

Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach

Kai Zhao, Qiyu Kang, Yang Song +3

Graph neural networks (GNNs) are vulnerable to adversarial perturbations, including those that affect both node features and graph topology. This paper investigates GNNs derived fr…

cs.LG2023★ 1 cited

Graph Neural Convection-Diffusion with Heterophily

Kai Zhao, Qiyu Kang, Yang Song +3

Graph neural networks (GNNs) have shown promising results across various graph learning tasks, but they often assume homophily, which can result in poor performance on heterophilic…

cs.LG2023

Node Embedding from Hamiltonian Information Propagation in Graph Neural Networks

Qiyu Kang, Kai Zhao, Yang Song +3

Graph neural networks (GNNs) have achieved success in various inference tasks on graph-structured data. However, common challenges faced by many GNNs in the literature include the…

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