42 citations · 82 across the 10 of their papers we have counts for
10 papers
Temporal Inductive Path Neural Network for Temporal Knowledge Graph Reasoning
Hao Dong, Pengyang Wang, Meng Xiao +3
Temporal Knowledge Graph (TKG) is an extension of traditional Knowledge Graph (KG) that incorporates the dimension of time. Reasoning on TKGs is a crucial task that aims to predict…
Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation
Meng Xiao, Min Wu, Ziyue Qiao +4
The objective of topic inference in research proposals aims to obtain the most suitable disciplinary division from the discipline system defined by a funding agency. The agency wil…
Data Augmentation for Graph Convolutional Network on Semi-Supervised Classification
Zhengzheng Tang, Ziyue Qiao, Xuehai Hong +4
Data augmentation aims to generate new and synthetic features from the original data, which can identify a better representation of data and improve the performance and generalizab…
TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution
Fayaz Ali Dharejo, Farah Deeba, Yuanchun Zhou +5
Single Image Super-resolution (SISR) produces high-resolution images with fine spatial resolutions from aremotely sensed image with low spatial resolution. Recently, deep learning…
LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding
Zhiyuan Ning, Ziyue Qiao, Hao Dong +2
Knowledge graph embedding (KGE) models learn to project symbolic entities and relations into a continuous vector space based on the observed triplets. However, existing KGE models…
Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective
Dongjie Wang, Pengyang Wang, Kunpeng Liu +3
In this paper, we study the problem of mobile user profiling, which is a critical component for quantifying users' characteristics in the human mobility modeling pipeline. Human mo…
Context-Enhanced Entity and Relation Embedding for Knowledge Graph Completion
Ziyue Qiao, Zhiyuan Ning, Yi Du +1
Most researches for knowledge graph completion learn representations of entities and relations to predict missing links in incomplete knowledge graphs. However, these methods fail…
Tree Structure-Aware Graph Representation Learning via Integrated Hierarchical Aggregation and Relational Metric Learning
Ziyue Qiao, Pengyang Wang, Yanjie Fu +3
While Graph Neural Network (GNN) has shown superiority in learning node representations of homogeneous graphs, leveraging GNN on heterogeneous graphs remains a challenging problem.…
Approximations and Bounds for (n, k) Fork-Join Queues: A Linear Transformation Approach
Huajin Wang, Jianhui Li, Zhihong Shen +1
Compared to basic fork-join queues, a job in (n, k) fork-join queues only needs its k out of all n sub-tasks to be finished. Since (n, k) fork-join queues are prevalent in popular…
Heterogeneous Metric Learning with Content-based Regularization for Software Artifact Retrieval
Liang Wu, Hui Xiong, Liang Du +6
The problem of software artifact retrieval has the goal to effectively locate software artifacts, such as a piece of source code, in a large code repository. This problem has been…