most citedMentorGNN: Deriving Curriculum for Pre-Training GNNs

3 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting

Xiao Lin, Zhining Liu, Dongqi Fu +2

Multivariate Time Series (MTS) forecasting is a fundamental task with numerous real-world applications, such as transportation, climate, and epidemiology. While a myriad of powerfu…

cs.LG20242 cited

Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection

Dongqi Fu, Yada Zhu, Hanghang Tong +3

Understanding the causal interaction of time series variables can contribute to time series data analysis for many real-world applications, such as climate forecasting and extreme…

cs.LG20243 cited

VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections

Dongqi Fu, Zhigang Hua, Yan Xie +7

Graph transformer has been proven as an effective graph learning method for its adoption of attention mechanism that is capable of capturing expressive representations from complex…

cs.LG20223 cited

MentorGNN: Deriving Curriculum for Pre-Training GNNs

Dawei Zhou, Lecheng Zheng, Dongqi Fu +2

Graph pre-training strategies have been attracting a surge of attention in the graph mining community, due to their flexibility in parameterizing graph neural networks (GNNs) witho…

cs.CR20221 cited

Privacy-preserving Graph Analytics: Secure Generation and Federated Learning

Dongqi Fu, Jingrui He, Hanghang Tong +1

Directly motivated by security-related applications from the Homeland Security Enterprise, we focus on the privacy-preserving analysis of graph data, which provides the crucial cap…