94 citations · 122 across the 8 of their papers we have counts for
8 papers
AceMap: Knowledge Discovery through Academic Graph
Xinbing Wang, Luoyi Fu, Xiaoying Gan +23
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering sear…
Graph Out-of-Distribution Generalization with Controllable Data Augmentation
Bin Lu, Xiaoying Gan, Ze Zhao +4
Graph Neural Network (GNN) has demonstrated extraordinary performance in classifying graph properties. However, due to the selection bias of training and testing data (e.g., traini…
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
Bin Lu, Xiaoying Gan, Lina Yang +3
With the tremendous expansion of graphs data, node classification shows its great importance in many real-world applications. Existing graph neural network based methods mainly foc…
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer
Bin Lu, Xiaoying Gan, Weinan Zhang +3
Spatio-temporal graph learning is a key method for urban computing tasks, such as traffic flow, taxi demand and air quality forecasting. Due to the high cost of data collection, so…
DeCOM: Decomposed Policy for Constrained Cooperative Multi-Agent Reinforcement Learning
Zhaoxing Yang, Rong Ding, Haiming Jin +5
In recent years, multi-agent reinforcement learning (MARL) has presented impressive performance in various applications. However, physical limitations, budget restrictions, and man…
High-Order Relation Construction and Mining for Graph Matching
Hui Xu, Liyao Xiang, Youmin Le +4
Graph matching pairs corresponding nodes across two or more graphs. The problem is difficult as it is hard to capture the structural similarity across graphs, especially on large g…
Maximum Value Matters: Finding Hot Topics in Scholarly Fields
Jinghao Zhao, Hao Wu, Fengyu Deng +4
Finding hot topics in scholarly fields can help researchers to keep up with the latest concepts, trends, and inventions in their field of interest. Due to the rarity of complete la…
Theoretical Analysis of Cyclic Frequency Domain Noise and Feature Detection for Cognitive Radio Systems
Gan Xiaoying, Shan Da, Zhou Yuan +2
In cognitive radio systems, cyclostationary feature detection plays an important role in spectrum sensing, especially in low SNR cases. To configure the detection threshold under a…