Cover Image

Multi-Level Service Performance Forecasting via Spatiotemporal Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xue, Zhihao, Zi, Yun, Qi, Nia, Gong, Ming, Zou, Yujun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Neural Network and Transformer Integration for Unsupervised System Anomaly Discovery
by: Zi, Yun, et al.
Published: (2025)

Autonomous Resource Management in Microservice Systems via Reinforcement Learning
by: Zou, Yujun, et al.
Published: (2025)

Leveraging Spatiotemporal Graph Neural Networks for Multi-Store Sales Forecasting
by: Singh, Manish, et al.
Published: (2025)

Structure-Learnable Adapter Fine-Tuning for Parameter-Efficient Large Language Models
by: Gong, Ming, et al.
Published: (2025)

Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks
by: Einizade, Aref, et al.
Published: (2024)

Dynamic Modes as Time Representation for Spatiotemporal Forecasting
by: Kong, Menglin, et al.
Published: (2025)

T-Graphormer: Using Transformers for Spatiotemporal Forecasting
by: Bai, Hao Yuan, et al.
Published: (2025)

Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation
by: Jing, Baoyu, et al.
Published: (2024)

Transformer with Koopman-Enhanced Graph Convolutional Network for Spatiotemporal Dynamics Forecasting
by: Wang, Zekai, et al.
Published: (2025)

Variational Mode-Driven Graph Convolutional Network for Spatiotemporal Traffic Forecasting
by: Ahmad, Osama, et al.
Published: (2024)

Spatiotemporal Multi-Task Graph Transformer for Trip-Level Transit Prediction
by: Yusuf, Oluwaleke, et al.
Published: (2026)

Over-squashing in Spatiotemporal Graph Neural Networks
by: Marisca, Ivan, et al.
Published: (2025)

Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks
by: Liu, Xuyuan, et al.
Published: (2024)

Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks
by: Gu, Jing, et al.
Published: (2024)

Spatiotemporal Graph Convolutional Recurrent Neural Network Model for Citywide Air Pollution Forecasting
by: Le, Van-Duc, et al.
Published: (2023)

Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks
by: Hirabayashi, Yuta, et al.
Published: (2026)

Graph Neural Networks for Electricity Load Forecasting
by: Campagne, Eloi, et al.
Published: (2025)

Probabilistic Demand Forecasting with Graph Neural Networks
by: Kozodoi, Nikita, et al.
Published: (2024)

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
by: Huang, Zheng, et al.
Published: (2024)

Incident-Guided Spatiotemporal Traffic Forecasting
by: Fan, Lixiang, et al.
Published: (2026)

Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms
by: Hong, Sungchul, et al.
Published: (2023)

Towards Explaining Deep Neural Network Compression Through a Probabilistic Latent Space
by: Mozafari-Nia, Mahsa, et al.
Published: (2024)

One Node Per User: Node-Level Federated Learning for Graph Neural Networks
by: Gao, Zhidong, et al.
Published: (2024)

Spatiotemporal Covariance Neural Networks
by: Cavallo, Andrea, et al.
Published: (2024)

Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)

Spatiotemporal-Augmented Graph Neural Networks for Human Mobility Simulation
by: Wang, Yu, et al.
Published: (2023)

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
by: Oskarsson, Joel, et al.
Published: (2024)

Uncertainty Quantification of Spatiotemporal Travel Demand with Probabilistic Graph Neural Networks
by: Wang, Qingyi, et al.
Published: (2023)

AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
by: Zhang, Zhongyue, et al.
Published: (2026)

SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
by: Zhuang, Dingyi, et al.
Published: (2024)

ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
by: Cai, Wanlin, et al.
Published: (2024)

Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective
by: Li, Gaotang, et al.
Published: (2023)

P-DROP: Poisson-Based Dropout for Graph Neural Networks
by: Yun, Hyunsik
Published: (2025)

Relating-Up: Advancing Graph Neural Networks through Inter-Graph Relationships
by: Zou, Qi, et al.
Published: (2024)

Graph Neural Networks in Wind Power Forecasting
by: Castellano, Javier, et al.
Published: (2025)

Non-Intrusive Graph-Based Bot Detection for E-Commerce Using Inductive Graph Neural Networks
by: Zhao, Sichen, et al.
Published: (2026)

Hierarchical Graph Networks for Accurate Weather Forecasting via Lightweight Training
by: Bailie, Thomas, et al.
Published: (2025)

FANFOLD: Graph Normalizing Flows-driven Asymmetric Network for Unsupervised Graph-Level Anomaly Detection
by: Cao, Rui, et al.
Published: (2024)

UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction
by: Yu, Dahai, et al.
Published: (2025)

Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers
by: Lu, Yiwei, et al.
Published: (2024)