activity
20242026
most citedTensor-view Topological Graph Neural Network

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Signed Graph Pre-Training and Prompt Learning

Zihan Mei, Rong Pan, Yuzhou Chen +1

Signed graphs arise in trust--distrust networks, financial correlation systems, biological interaction graphs, and many other domains in which edges can be positive or negative and…

cs.LG2025

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation

Tao Wen, Elynn Chen, Yuzhou Chen +1

Graph Neural Networks (GNNs) have recently become the predominant tools for studying graph data. Despite state-of-the-art performance on graph classification tasks, GNNs are overwh…

cs.LG2024★ 1 cited

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting

Linghang Kong, Elynn Chen, Yuzhou Chen +1

Multi-dimensional time series data, such as matrix and tensor-variate time series, are increasingly prevalent in fields such as economics, finance, and climate science. Traditional…

cs.LG2024

Conditional Uncertainty Quantification for Tensorized Topological Neural Networks

Yujia Wu, Bo Yang, Yang Zhao +3

Graph Neural Networks (GNNs) have become the de facto standard for analyzing graph-structured data, leveraging message-passing techniques to capture both structural and node featur…

cs.LG2024

Conditional Prediction ROC Bands for Graph Classification

Yujia Wu, Bo Yang, Elynn Chen +2

Graph classification in medical imaging and drug discovery requires accuracy and robust uncertainty quantification. To address this need, we introduce Conditional Prediction ROC (C…

cs.LG2024

Tensor-Fused Multi-View Graph Contrastive Learning

Yujia Wu, Junyi Mo, Elynn Chen +1

Graph contrastive learning (GCL) has emerged as a promising approach to enhance graph neural networks' (GNNs) ability to learn rich representations from unlabeled graph-structured…

cs.LG2024★ 1 cited

Tensor-view Topological Graph Neural Network

Tao Wen, Elynn Chen, Yuzhou Chen

Graph classification is an important learning task for graph-structured data. Graph neural networks (GNNs) have recently gained growing attention in graph learning and have shown s…