78 citations · 140 across the 6 of their papers we have counts for
6 papers
KMF: Knowledge-Aware Multi-Faceted Representation Learning for Zero-Shot Node Classification
Likang Wu, Junji Jiang, Hongke Zhao +4
Recently, Zero-Shot Node Classification (ZNC) has been an emerging and crucial task in graph data analysis. This task aims to predict nodes from unseen classes which are unobserved…
Deep Graph Representation Learning and Optimization for Influence Maximization
Chen Ling, Junji Jiang, Junxiang Wang +5
Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great…
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
Yuyang Gao, Siyi Gu, Junji Jiang +3
As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metr…
DeepGAR: Deep Graph Learning for Analogical Reasoning
Chen Ling, Tanmoy Chowdhury, Junji Jiang +4
Analogical reasoning is the process of discovering and mapping correspondences from a target subject to a base subject. As the most well-known computational method of analogical re…
Source Localization of Graph Diffusion via Variational Autoencoders for Graph Inverse Problems
Chen Ling, Junji Jiang, Junxiang Wang +1
Graph diffusion problems such as the propagation of rumors, computer viruses, or smart grid failures are ubiquitous and societal. Hence it is usually crucial to identify diffusion…
An Invertible Graph Diffusion Neural Network for Source Localization
Junxiang Wang, Junji Jiang, Liang Zhao
Localizing the source of graph diffusion phenomena, such as misinformation propagation, is an important yet extremely challenging task. Existing source localization models typicall…