Search Results for author: Xuefei Zhang

Found 7 papers, 2 papers with code

CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks

2 code implementations ICLR 2021 Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei

In this paper, we distinguish the \textit{representational} and the \textit{correlational} roles played by the graphs in node-level prediction tasks, and we investigate how Graph Neural Network (GNN) models can effectively leverage both types of information.

RelationRS: Relationship Representation Network for Object Detection in Aerial Images

no code implementations13 Oct 2021 Zhiming Liu, Xuefei Zhang, Chongyang Liu, Hao Wang, Chao Sun, Bin Li, Weifeng Sun, Pu Huang, Qingjun Li, Yu Liu, Haipeng Kuang, Jihong Xiu

To address these issues, we propose a relationship representation network for object detection in aerial images (RelationRS): 1) Firstly, multi-scale features are fused and enhanced by a dual relationship module (DRM) with conditional convolution.

Object object-detection +1

Physical-layer Adversarial Robustness for Deep Learning-based Semantic Communications

no code implementations12 May 2023 Guoshun Nan, Zhichun Li, Jinli Zhai, Qimei Cui, Gong Chen, Xin Du, Xuefei Zhang, Xiaofeng Tao, Zhu Han, Tony Q. S. Quek

We argue that central to the success of ESC is the robust interpretation of conveyed semantics at the receiver side, especially for security-critical applications such as automatic driving and smart healthcare.

Adversarial Robustness

Transport-Hub-Aware Spatial-Temporal Adaptive Graph Transformer for Traffic Flow Prediction

1 code implementation12 Oct 2023 Xiao Xu, Lei Zhang, Bailong Liu, Zhizhen Liang, Xuefei Zhang

Finally, we design an extra spatial-temporal knowledge distillation module for incremental learning of traffic flow prediction tasks.

Incremental Learning Knowledge Distillation

A Flexible Latent Space Model for Multilayer Networks

no code implementations ICML 2020 Xuefei Zhang, Songkai Xue, Ji Zhu

Entities often interact with each other through multiple types of relations, which are often represented as multilayer networks.

Cannot find the paper you are looking for? You can Submit a new open access paper.