Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
Fuente:
arXiv
Saved in:
| Main Authors: | Jin, Ming, Shi, Guangsi, Li, Yuan-Fang, Xiong, Bo, Zhou, Tian, Salim, Flora D., Zhao, Liang, Wu, Lingfei, Wen, Qingsong, Pan, Shirui |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
by: Shi, Guangsi, et al.
Published: (2023)
by: Shi, Guangsi, et al.
Published: (2023)
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
by: Jin, Ming, et al.
Published: (2023)
by: Jin, Ming, et al.
Published: (2023)
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
by: Hu, Jiaxi, et al.
Published: (2024)
by: Hu, Jiaxi, et al.
Published: (2024)
Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2025)
by: Liang, Yuxuan, et al.
Published: (2025)
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)
by: Pan, Sheng, et al.
Published: (2026)
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
by: Jin, Ming, et al.
Published: (2023)
by: Jin, Ming, et al.
Published: (2023)
Foundation Models for Time Series Analysis: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2024)
by: Liang, Yuxuan, et al.
Published: (2024)
Towards Neural Scaling Laws for Time Series Foundation Models
by: Yao, Qingren, et al.
Published: (2024)
by: Yao, Qingren, et al.
Published: (2024)
Breaking the Regional Barrier: Inductive Semantic Topology Learning for Worldwide Air Quality Forecasting
by: Cui, Zhiqing, et al.
Published: (2026)
by: Cui, Zhiqing, et al.
Published: (2026)
A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
by: Yang, Yiyuan, et al.
Published: (2024)
by: Yang, Yiyuan, et al.
Published: (2024)
ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
by: Huang, Bosong, et al.
Published: (2025)
by: Huang, Bosong, et al.
Published: (2025)
Continuous Evolution Pool: Taming Recurring Concept Drift in Online Time Series Forecasting
by: Zhan, Tianxiang, et al.
Published: (2025)
by: Zhan, Tianxiang, et al.
Published: (2025)
EventTSF: Event-Aware Non-Stationary Time Series Forecasting
by: Ge, Yunfeng, et al.
Published: (2025)
by: Ge, Yunfeng, et al.
Published: (2025)
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
by: Qiao, Zhongzheng, et al.
Published: (2026)
by: Qiao, Zhongzheng, et al.
Published: (2026)
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
by: Cheng, Hao, et al.
Published: (2024)
by: Cheng, Hao, et al.
Published: (2024)
Time-VLM: Exploring Multimodal Vision-Language Models for Augmented Time Series Forecasting
by: Zhong, Siru, et al.
Published: (2025)
by: Zhong, Siru, et al.
Published: (2025)
TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
by: Hu, Yifan, et al.
Published: (2025)
by: Hu, Yifan, et al.
Published: (2025)
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
by: Liu, Qingxiang, et al.
Published: (2024)
by: Liu, Qingxiang, et al.
Published: (2024)
Graph Navier Stokes Networks
by: Zhao, Zexing, et al.
Published: (2026)
by: Zhao, Zexing, et al.
Published: (2026)
AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs
by: Dang, Ting, et al.
Published: (2026)
by: Dang, Ting, et al.
Published: (2026)
Position: What Can Large Language Models Tell Us about Time Series Analysis
by: Jin, Ming, et al.
Published: (2024)
by: Jin, Ming, et al.
Published: (2024)
Online GNN Evaluation Under Test-time Graph Distribution Shifts
by: Zheng, Xin, et al.
Published: (2024)
by: Zheng, Xin, et al.
Published: (2024)
GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network
by: Chen, Weiqi, et al.
Published: (2024)
by: Chen, Weiqi, et al.
Published: (2024)
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting
by: Xue, Wang, et al.
Published: (2023)
by: Xue, Wang, et al.
Published: (2023)
Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects
by: Zhang, Kexin, et al.
Published: (2023)
by: Zhang, Kexin, et al.
Published: (2023)
Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)
by: Hu, Jiaxi, et al.
Published: (2024)
TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting
by: Hu, Jiaxi, et al.
Published: (2024)
by: Hu, Jiaxi, et al.
Published: (2024)
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
by: Lyu, Sisuo, et al.
Published: (2025)
by: Lyu, Sisuo, et al.
Published: (2025)
DRIFT-Net: A Spectral--Coupled Neural Operator for PDEs Learning
by: Li, Jiayi, et al.
Published: (2025)
by: Li, Jiayi, et al.
Published: (2025)
A Dynamic Stiefel Graph Neural Network for Efficient Spatio-Temporal Time Series Forecasting
by: Zheng, Jiankai, et al.
Published: (2025)
by: Zheng, Jiankai, et al.
Published: (2025)
SDE-Attention: Latent Attention in SDE-RNNs for Irregularly Sampled Time Series with Missing Data
by: Fang, Yuting, et al.
Published: (2025)
by: Fang, Yuting, et al.
Published: (2025)
Unlocking the Power of LSTM for Long Term Time Series Forecasting
by: Kong, Yaxuan, et al.
Published: (2024)
by: Kong, Yaxuan, et al.
Published: (2024)
Multi-Order Wavelet Derivative Transform for Deep Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2025)
by: Zhou, Ziyu, et al.
Published: (2025)
Toward Physics-guided Time Series Embedding
by: Hu, Jiaxi, et al.
Published: (2024)
by: Hu, Jiaxi, et al.
Published: (2024)
Benchmarks and Custom Package for Energy Forecasting
by: Wang, Zhixian, et al.
Published: (2023)
by: Wang, Zhixian, et al.
Published: (2023)
AION: Next-Generation Tasks and Practical Harness for Time Series
by: Zhan, Tianxiang, et al.
Published: (2026)
by: Zhan, Tianxiang, et al.
Published: (2026)
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting System
by: Li, Mingjie, et al.
Published: (2022)
by: Li, Mingjie, et al.
Published: (2022)
STC-ViT: Spatio Temporal Continuous Vision Transformer for Medium-range Global Weather Forecasting
by: Saleem, Hira, et al.
Published: (2024)
by: Saleem, Hira, et al.
Published: (2024)
TimeOmni-1: Incentivizing Complex Reasoning with Time Series in Large Language Models
by: Guan, Tong, et al.
Published: (2025)
by: Guan, Tong, et al.
Published: (2025)
Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning
by: Yang, Ruiyi, et al.
Published: (2025)
by: Yang, Ruiyi, et al.
Published: (2025)
Similar Items
-
Towards Complex Dynamic Physics System Simulation with Graph Neural ODEs
by: Shi, Guangsi, et al.
Published: (2023) -
A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
by: Jin, Ming, et al.
Published: (2023) -
Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
by: Hu, Jiaxi, et al.
Published: (2024) -
Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey
by: Liang, Yuxuan, et al.
Published: (2025) -
LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)