4 citations · 14 across the 8 of their papers we have counts for
8 papers
Union Subgraph Neural Networks
Jiaxing Xu, Aihu Zhang, Qingtian Bian +2
Graph Neural Networks (GNNs) are widely used for graph representation learning in many application domains. The expressiveness of vanilla GNNs is upper-bounded by 1-dimensional Wei…
Data-Driven Network Neuroscience: On Data Collection and Benchmark
Jiaxing Xu, Yunhan Yang, David Tse Jung Huang +7
This paper presents a comprehensive and quality collection of functional human brain network data for potential research in the intersection of neuroscience, machine learning, and…
A Class-Aware Representation Refinement Framework for Graph Classification
Jiaxing Xu, Jinjie Ni, Yiping Ke
Graph Neural Networks (GNNs) are widely used for graph representation learning. Despite its prevalence, GNN suffers from two drawbacks in the graph classification task, the neglect…
Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions
Tianbo Li, Tianze Luo, Yiping Ke +1
Attributed event sequences are commonly encountered in practice. A recent research line focuses on incorporating neural networks with the statistical model -- marked point processe…
Subdomain Adaptation with Manifolds Discrepancy Alignment
Pengfei Wei, Yiping Ke, Xinghua Qu +1
Reducing domain divergence is a key step in transfer learning problems. Existing works focus on the minimization of global domain divergence. However, two domains may consist of se…
Stochastic Variance Reduced Riemannian Eigensolver
Zhiqiang Xu, Yiping Ke
We study the stochastic Riemannian gradient algorithm for matrix eigen-decomposition. The state-of-the-art stochastic Riemannian algorithm requires the learning rate to decay to ze…
Efficient Processing of Reachability and Time-Based Path Queries in a Temporal Graph
Huanhuan Wu, Yuzhen Huang, James Cheng +2
A temporal graph is a graph in which vertices communicate with each other at specific time, e.g., calls at 11 a.m. and talks for 7 minutes, which is modeled by an edge from…
Detecting Priming News Events
Di Wu, Yiping Ke, Jeffrey Xu Yu +1
We study a problem of detecting priming events based on a time series index and an evolving document stream. We define a priming event as an event which triggers abnormal movements…