600 citations · 1.3k across the 42 of their papers we have counts for
13 papers · 1 filter
A Self-supervised Mixed-curvature Graph Neural Network
Li Sun, Zhongbao Zhang, Junda Ye +4
Graph representation learning received increasing attentions in recent years. Most of existing methods ignore the complexity of the graph structures and restrict graphs in a single…
Pre-training Recommender Systems via Reinforced Attentive Multi-relational Graph Neural Network
Xiaohan Li, Zhiwei Liu, Stephen Guo +4
Recently, Graph Neural Networks (GNNs) have proven their effectiveness for recommender systems. Existing studies have applied GNNs to capture collaborative relations in the data. H…
Federated Social Recommendation with Graph Neural Network
Zhiwei Liu, Liangwei Yang, Ziwei Fan +2
Recommender systems have become prosperous nowadays, designed to predict users' potential interests in items by learning embeddings. Recent developments of the Graph Neural Network…
Ideal spin hydrodynamics from Wigner function approach
Hao-Hao Peng, Jun-Jie Zhang, Xin-Li Sheng +1
Based on the Wigner function in local equilibrium, we derive hydrodynamical quantities for a system of polarized spin-1/2 particles: the particle number current density, the energy…
A Robust and Generalized Framework for Adversarial Graph Embedding
Jianxin Li, Xingcheng Fu, Hao Peng +5
Graph embedding is essential for graph mining tasks. With the prevalence of graph data in real-world applications, many methods have been proposed in recent years to learn high-qua…
Noised Consistency Training for Text Summarization
Junnan Liu, Qianren Mao, Bang Liu +3
Neural abstractive summarization methods often require large quantities of labeled training data. However, labeling large amounts of summarization data is often prohibitive due to…