337 citations · 559 across the 13 of their papers we have counts for
13 papers
Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting
Yusheng Zhao, Xiao Luo, Wei Ju +3
This paper studies the problem of traffic flow forecasting, which aims to predict future traffic conditions on the basis of road networks and traffic conditions in the past. The pr…
Redundancy-Free Self-Supervised Relational Learning for Graph Clustering
Si-Yu Yi, Wei Ju, Yifang Qin +4
Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable atte…
RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification
Zhengyang Mao, Wei Ju, Yifang Qin +2
Graph classification is a crucial task in many real-world multimedia applications, where graphs can represent various multimedia data types such as images, videos, and social netwo…
Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts
Siyu Yi, Zhengyang Mao, Wei Ju +4
Graph classification, aiming at learning the graph-level representations for effective class assignments, has received outstanding achievements, which heavily relies on high-qualit…
Learning on Graphs under Label Noise
Jingyang Yuan, Xiao Luo, Yifang Qin +3
Node classification on graphs is a significant task with a wide range of applications, including social analysis and anomaly detection. Even though graph neural networks (GNNs) hav…
Towards Semi-supervised Universal Graph Classification
Xiao Luo, Yusheng Zhao, Yifang Qin +2
Graph neural networks have pushed state-of-the-arts in graph classifications recently. Typically, these methods are studied within the context of supervised end-to-end training, wh…
Learning Graph ODE for Continuous-Time Sequential Recommendation
Yifang Qin, Wei Ju, Hongjun Wu +2
Sequential recommendation aims at understanding user preference by capturing successive behavior correlations, which are usually represented as the item purchasing sequences based…
A Diffusion model for POI recommendation
Yifang Qin, Hongjun Wu, Wei Ju +2
Next Point-of-Interest (POI) recommendation is a critical task in location-based services that aim to provide personalized suggestions for the user's next destination. Previous wor…
A Comprehensive Survey on Deep Graph Representation Learning
Wei Ju, Zheng Fang, Yiyang Gu +13
Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been…
Kernel-based Substructure Exploration for Next POI Recommendation
Wei Ju, Yifang Qin, Ziyue Qiao +4
Point-of-Interest (POI) recommendation, which benefits from the proliferation of GPS-enabled devices and location-based social networks (LBSNs), plays an increasingly important rol…
GLCC: A General Framework for Graph-Level Clustering
Wei Ju, Yiyang Gu, Binqi Chen +5
This paper studies the problem of graph-level clustering, which is a novel yet challenging task. This problem is critical in a variety of real-world applications such as protein cl…
Progress Notes Classification and Keyword Extraction using Attention-based Deep Learning Models with BERT
Matthew Tang, Priyanka Gandhi, Md Ahsanul Kabir +3
Various deep learning algorithms have been developed to analyze different types of clinical data including clinical text classification and extracting information from 'free text'…
Biomedical Document Clustering and Visualization based on the Concepts of Diseases
Setu Shah, Xiao Luo
Document clustering is a text mining technique used to provide better document search and browsing in digital libraries or online corpora. A lot of research has been done on biomed…