39 citations · 62 across the 8 of their papers we have counts for
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cs.LG2020
Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding
Lin Lan, Pinghui Wang, Xuefeng Du +3
We study the problem of node classification on graphs with few-shot novel labels, which has two distinctive properties: (1) There are novel labels to emerge in the graph; (2) The n…
cs.LG2019★ 9 cited
Meta Reinforcement Learning with Task Embedding and Shared Policy
Lin Lan, Zhenguo Li, Xiaohong Guan +1
Despite significant progress, deep reinforcement learning (RL) suffers from data-inefficiency and limited generalization. Recent efforts apply meta-learning to learn a meta-learner…
cs.LG2019
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions
Nuo Xu, Pinghui Wang, Long Chen +2
Predicting interactions between structured entities lies at the core of numerous tasks such as drug regimen and new material design. In recent years, graph neural networks have bec…