43 citations · 181 across the 27 of their papers we have counts for
7 papers · 1 filter
Link Prediction with Non-Contrastive Learning
William Shiao, Zhichun Guo, Tong Zhao +3
A recent focal area in the space of graph neural networks (GNNs) is graph self-supervised learning (SSL), which aims to derive useful node representations without labeled data. Not…
Reciprocity, Homophily, and Social Network Effects in Pictorial Communication: A Case Study of Bitmoji Stickers
Julie Jiang, Ron Dotsch, Mireia Triguero Roura +4
Pictorial emojis and stickers are commonly used in online social networking to facilitate and aid communications. We delve into the use of Bitmoji stickers, a highly expressive for…
Linkless Link Prediction via Relational Distillation
Zhichun Guo, William Shiao, Shichang Zhang +4
Graph Neural Networks (GNNs) have shown exceptional performance in the task of link prediction. Despite their effectiveness, the high latency brought by non-trivial neighborhood da…
Empowering Graph Representation Learning with Test-Time Graph Transformation
Wei Jin, Tong Zhao, Jiayuan Ding +3
As powerful tools for representation learning on graphs, graph neural networks (GNNs) have facilitated various applications from drug discovery to recommender systems. Nevertheless…
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Xiaotian Han, Tong Zhao, Yozen Liu +2
Training graph neural networks (GNNs) on large graphs is complex and extremely time consuming. This is attributed to overheads caused by sparse matrix multiplication, which are sid…
Flashlight: Scalable Link Prediction with Effective Decoders
Yiwei Wang, Bryan Hooi, Yozen Liu +3
Link prediction (LP) has been recognized as an important task in graph learning with its broad practical applications. A typical application of LP is to retrieve the top scoring ne…
GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games
Shichang Zhang, Yozen Liu, Neil Shah +1
Explaining machine learning models is an important and increasingly popular area of research interest. The Shapley value from game theory has been proposed as a prime approach to c…