Saved in:
| Main Authors: | Liu, Zhipeng, Duan, Peibo, Tang, Xuan, Li, Baixin, Huang, Yongsheng, Geng, Mingyang, Zhang, Changsheng, Zhang, Bin, Wang, Binwu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.06680 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2026)
by: Liu, Zhipeng, et al.
Published: (2026)
DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2025)
by: Liu, Zhipeng, et al.
Published: (2025)
A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
by: Liu, Zhipeng, et al.
Published: (2025)
by: Liu, Zhipeng, et al.
Published: (2025)
CogniSNN: An Exploration to Random Graph Architecture based Spiking Neural Networks with Enhanced Depth-Scalability and Path-Plasticity
by: Huang, Yongsheng, et al.
Published: (2025)
by: Huang, Yongsheng, et al.
Published: (2025)
TimeFormer: Capturing Temporal Relationships of Deformable 3D Gaussians for Robust Reconstruction
by: Jiang, DaDong, et al.
Published: (2024)
by: Jiang, DaDong, et al.
Published: (2024)
CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
by: Huang, Yongsheng, et al.
Published: (2025)
by: Huang, Yongsheng, et al.
Published: (2025)
Gated Fusion Enhanced Multi-Scale Hierarchical Graph Convolutional Network for Stock Movement Prediction
by: Xue, Xiaosha, et al.
Published: (2025)
by: Xue, Xiaosha, et al.
Published: (2025)
MorphSNN: Adaptive Graph Diffusion and Structural Plasticity for Spiking Neural Networks
by: Huang, Yongsheng, et al.
Published: (2026)
by: Huang, Yongsheng, et al.
Published: (2026)
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
by: Wang, Yuxuan, et al.
Published: (2024)
by: Wang, Yuxuan, et al.
Published: (2024)
LLM-PS: Empowering Large Language Models for Time Series Forecasting with Temporal Patterns and Semantics
by: Tang, Jialiang, et al.
Published: (2025)
by: Tang, Jialiang, et al.
Published: (2025)
QuiZSF: A Retrieval-Augmented Framework for Zero-Shot Time Series Forecasting
by: Ma, Shichao, et al.
Published: (2025)
by: Ma, Shichao, et al.
Published: (2025)
WeatherFormer: Empowering Global Numerical Weather Forecasting with Space-Time Transformer
by: Gong, Junchao, et al.
Published: (2024)
by: Gong, Junchao, et al.
Published: (2024)
TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts
by: Ma, Xiaowen, et al.
Published: (2025)
by: Ma, Xiaowen, et al.
Published: (2025)
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
by: Le, Xuan-May, et al.
Published: (2024)
by: Le, Xuan-May, et al.
Published: (2024)
To See Far, Look Close: Evolutionary Forecasting for Long-term Time Series
by: Ma, Jiaming, et al.
Published: (2026)
by: Ma, Jiaming, et al.
Published: (2026)
PHAT: Modeling Period Heterogeneity for Multivariate Time Series Forecasting
by: Ma, Jiaming, et al.
Published: (2026)
by: Ma, Jiaming, et al.
Published: (2026)
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis
by: Ni, Zelin, et al.
Published: (2023)
by: Ni, Zelin, et al.
Published: (2023)
Sentinel: Multi-Patch Transformer with Temporal and Channel Attention for Time Series Forecasting
by: Villaboni, Davide, et al.
Published: (2025)
by: Villaboni, Davide, et al.
Published: (2025)
PSformer: Parameter-efficient Transformer with Segment Attention for Time Series Forecasting
by: Wang, Yanlong, et al.
Published: (2024)
by: Wang, Yanlong, et al.
Published: (2024)
Temporal Attention Evolutional Graph Convolutional Network for Multivariate Time Series Forecasting
by: Zhao, Xinlong, et al.
Published: (2025)
by: Zhao, Xinlong, et al.
Published: (2025)
LightGTS-Cov: Covariate-Enhanced Time Series Forecasting
by: Shang, Yong, et al.
Published: (2026)
by: Shang, Yong, et al.
Published: (2026)
SageFormer: Series-Aware Framework for Long-term Multivariate Time Series Forecasting
by: Zhang, Zhenwei, et al.
Published: (2023)
by: Zhang, Zhenwei, et al.
Published: (2023)
ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks
by: Sun, Kai, et al.
Published: (2025)
by: Sun, Kai, et al.
Published: (2025)
Fusing Large Language Models with Temporal Transformers for Time Series Forecasting
by: Su, Chen, et al.
Published: (2025)
by: Su, Chen, et al.
Published: (2025)
HGTS-Former: Hierarchical HyperGraph Transformer for Multivariate Time Series Analysis
by: Si, Hao, et al.
Published: (2025)
by: Si, Hao, et al.
Published: (2025)
TwinFormer: A Dual-Level Transformer for Long-Sequence Time-Series Forecasting
by: Kumavat, Mahima, et al.
Published: (2025)
by: Kumavat, Mahima, et al.
Published: (2025)
Empowering Time Series Forecasting with LLM-Agents
by: Yeh, Chin-Chia Michael, et al.
Published: (2025)
by: Yeh, Chin-Chia Michael, et al.
Published: (2025)
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated Transformers
by: Chakraborty, Sanjay, et al.
Published: (2025)
by: Chakraborty, Sanjay, et al.
Published: (2025)
ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
by: Chen, Yuqi, et al.
Published: (2024)
by: Chen, Yuqi, et al.
Published: (2024)
DeepKoopFormer: A Koopman Enhanced Transformer Based Architecture for Time Series Forecasting
by: Forootani, Ali, et al.
Published: (2025)
by: Forootani, Ali, et al.
Published: (2025)
MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting
by: Du, Linfeng, et al.
Published: (2023)
by: Du, Linfeng, et al.
Published: (2023)
A Temporal Kolmogorov-Arnold Transformer for Time Series Forecasting
by: Genet, Remi, et al.
Published: (2024)
by: Genet, Remi, et al.
Published: (2024)
Learning Temporal Saliency for Time Series Forecasting with Cross-Scale Attention
by: Delibasoglu, Ibrahim, et al.
Published: (2025)
by: Delibasoglu, Ibrahim, et al.
Published: (2025)
Temporally Unified Adversarial Perturbations for Time Series Forecasting
by: Su, Ruixian, et al.
Published: (2026)
by: Su, Ruixian, et al.
Published: (2026)
VIFO: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion
by: Wang, Yanlong, et al.
Published: (2025)
by: Wang, Yanlong, et al.
Published: (2025)
U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
by: Kuleshov, Ilya, et al.
Published: (2026)
by: Kuleshov, Ilya, et al.
Published: (2026)
sTransformer: A Modular Approach for Extracting Inter-Sequential and Temporal Information for Time-Series Forecasting
by: Yin, Jiaheng, et al.
Published: (2024)
by: Yin, Jiaheng, et al.
Published: (2024)
Modeling Temporal Dependencies within the Target for Long-Term Time Series Forecasting
by: Xiong, Qi, et al.
Published: (2024)
by: Xiong, Qi, et al.
Published: (2024)
Not All Timesteps Matter Equally: Selective Alignment Knowledge Distillation for Spiking Neural Networks
by: Sun, Kai, et al.
Published: (2026)
by: Sun, Kai, et al.
Published: (2026)
Characteristic Root Analysis and Regularization for Linear Time Series Forecasting
by: Wang, Zheng, et al.
Published: (2025)
by: Wang, Zheng, et al.
Published: (2025)
Similar Items
-
We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2026) -
DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2025) -
A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
by: Liu, Zhipeng, et al.
Published: (2025) -
CogniSNN: An Exploration to Random Graph Architecture based Spiking Neural Networks with Enhanced Depth-Scalability and Path-Plasticity
by: Huang, Yongsheng, et al.
Published: (2025) -
TimeFormer: Capturing Temporal Relationships of Deformable 3D Gaussians for Robust Reconstruction
by: Jiang, DaDong, et al.
Published: (2024)