337 citations · 823 across the 46 of their papers we have counts for
14 papers · 1 filter
PGODE: Towards High-quality System Dynamics Modeling
Xiao Luo, Yiyang Gu, Huiyu Jiang +6
This paper studies the problem of modeling multi-agent dynamical systems, where agents could interact mutually to influence their behaviors. Recent research predominantly uses geom…
ALEX: Towards Effective Graph Transfer Learning with Noisy Labels
Jingyang Yuan, Xiao Luo, Yifang Qin +3
Graph Neural Networks (GNNs) have garnered considerable interest due to their exceptional performance in a wide range of graph machine learning tasks. Nevertheless, the majority of…
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…
FIMO: A Challenge Formal Dataset for Automated Theorem Proving
Chengwu Liu, Jianhao Shen, Huajian Xin +9
We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems. Designed t…
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…
TGNN: A Joint Semi-supervised Framework for Graph-level Classification
Wei Ju, Xiao Luo, Meng Qu +5
This paper studies semi-supervised graph classification, a crucial task with a wide range of applications in social network analysis and bioinformatics. Recent works typically adop…
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…
Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data
Bin Feng, Tenglong Ao, Zequn Liu +3
How to automatically synthesize natural-looking dance movements based on a piece of music is an incrementally popular yet challenging task. Most existing data-driven approaches req…