:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hou, Jinyan, Liu, Shan, Zhang, Ya, Qin, Haotong
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2403.00276
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Virtual Nodes Improve Long-term Traffic Prediction
by: Cao, Xiaoyang, et al.
Published: (2025)

CONTINA: Confidence Interval for Traffic Demand Prediction with Coverage Guarantee
by: Yang, Chao, et al.
Published: (2025)

Revisiting Node Affinity Prediction in Temporal Graphs
by: Feldman, Or, et al.
Published: (2025)

MSTIM: A MindSpore-Based Model for Traffic Flow Prediction
by: Qin, Weiqi, et al.
Published: (2025)

Position-Sensing Graph Neural Networks: Proactively Learning Nodes Relative Positions
by: Qin, Zhenyue, et al.
Published: (2021)

Scale-aware Message Passing For Graph Node Classification
by: Jiang, Qin, et al.
Published: (2024)

Meta Dynamic Graph for Traffic Flow Prediction
by: Zou, Yiqing, et al.
Published: (2026)

A Knowledge-Guided Cross-Modal Feature Fusion Model for Local Traffic Demand Prediction
by: Zhang, Lingyu, et al.
Published: (2025)

Neural Common Neighbor with Completion for Link Prediction
by: Wang, Xiyuan, et al.
Published: (2023)

Progressive Binarization with Semi-Structured Pruning for LLMs
by: Yan, Xianglong, et al.
Published: (2025)

BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes
by: Wang, Qian, et al.
Published: (2024)

Tokenphormer: Structure-aware Multi-token Graph Transformer for Node Classification
by: Zhou, Zijie, et al.
Published: (2024)

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification
by: Zaz, Brown, et al.
Published: (2026)

Learning from Yesterday's Error: An Efficient Online Learning Method for Traffic Demand Prediction
by: Huang, Xiannan, et al.
Published: (2026)

Diffusion on Graph: Augmentation of Graph Structure for Node Classification
by: Wang, Yancheng, et al.
Published: (2025)

Node-Time Conditional Prompt Learning In Dynamic Graphs
by: Yu, Xingtong, et al.
Published: (2024)

Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction
by: Du, Haotong, et al.
Published: (2024)

Graph Based Traffic Analysis and Delay Prediction
by: Borg, Gabriele, et al.
Published: (2024)

GraphSparseNet: a Novel Method for Large Scale Traffic Flow Prediction
by: Kong, Weiyang, et al.
Published: (2025)

STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
by: Luo, Xunlian, et al.
Published: (2023)

GraphLearner: Graph Node Clustering with Fully Learnable Augmentation
by: Yang, Xihong, et al.
Published: (2022)

RABot: Reinforcement-Guided Graph Augmentation for Imbalanced and Noisy Social Bot Detection
by: Zhang, Longlong, et al.
Published: (2026)

Bootstrap Latents of Nodes and Neighbors for Graph Self-Supervised Learning
by: Liu, Yunhui, et al.
Published: (2024)

FedGT: Federated Node Classification with Scalable Graph Transformer
by: Zhang, Zaixi, et al.
Published: (2024)

Air Traffic Controller Task Demand via Graph Neural Networks: An Interpretable Approach to Airspace Complexity
by: Henderson, Edward, et al.
Published: (2025)

Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach
by: Nie, Tong, et al.
Published: (2024)

IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model
by: Olug, Eren, et al.
Published: (2024)

Conformal Prediction: A Theoretical Note and Benchmarking Transductive Node Classification in Graphs
by: Maneriker, Pranav, et al.
Published: (2024)

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
by: Choi, Jeongwhan, et al.
Published: (2026)

PUMA: Efficient Continual Graph Learning for Node Classification with Graph Condensation
by: Liu, Yilun, et al.
Published: (2023)

Label Informed Contrastive Pretraining for Node Importance Estimation on Knowledge Graphs
by: Zhang, Tianyu, et al.
Published: (2024)

NTFormer: A Composite Node Tokenized Graph Transformer for Node Classification
by: Chen, Jinsong, et al.
Published: (2024)

Pure Node Selection for Imbalanced Graph Node Classification
by: Zeng, Fanlong, et al.
Published: (2025)

STLGRU: Spatio-Temporal Lightweight Graph GRU for Traffic Flow Prediction
by: Bhaumik, Kishor Kumar, et al.
Published: (2022)

Leverage Multi-source Traffic Demand Data Fusion with Transformer Model for Urban Parking Prediction
by: Huang, Yin, et al.
Published: (2024)

Global-Aware Enhanced Spatial-Temporal Graph Recurrent Networks: A New Framework For Traffic Flow Prediction
by: Liu, Haiyang, et al.
Published: (2024)

Node2Vec-DGI-EL: A Hierarchical Graph Representation Learning Model for Ingredient-Disease Association Prediction
by: Zhang, Leifeng, et al.
Published: (2025)

Node Role-Guided LLMs for Dynamic Graph Clustering
by: Li, Dongyuan, et al.
Published: (2026)

DynaSTy: A Framework for SpatioTemporal Node Attribute Prediction in Dynamic Graphs
by: Banerji, Namrata, et al.
Published: (2026)

TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks
by: Liu, Yezi, et al.
Published: (2024)