Imagen de Portada

SST: Multi-Scale Hybrid Mamba-Transformer Experts for Time Series Forecasting

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xu, Xiongxiao, Chen, Canyu, Liang, Yueqing, Huang, Baixiang, Bai, Guangji, Zhao, Liang, Shu, Kai
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection
por: Xu, Xiongxiao, et al.
Publicado: (2023)

Piecing It All Together: Verifying Multi-Hop Multimodal Claims
por: Wang, Haoran, et al.
Publicado: (2024)

Can Knowledge Editing Really Correct Hallucinations?
por: Huang, Baixiang, et al.
Publicado: (2024)

Scaling Teams or Scaling Time? Memory Enabled Lifelong Learning in LLM Multi-Agent Systems
por: Wu, Shanglin, et al.
Publicado: (2026)

Can Multimodal LLMs Perform Time Series Anomaly Detection?
por: Xu, Xiongxiao, et al.
Publicado: (2025)

ms-Mamba: Multi-scale Mamba for Time-Series Forecasting
por: Karadag, Yusuf Meric, et al.
Publicado: (2025)

LATST: Are Transformers Necessarily Complex for Time-Series Forecasting
por: Liang, Dizhen
Publicado: (2024)

StructPrune: Structured Global Pruning asymptotics with $\mathcal{O}(\sqrt{N})$ GPU Memory
por: Song, Xinyuan, et al.
Publicado: (2025)

A Mamba Foundation Model for Time Series Forecasting
por: Ma, Haoyu, et al.
Publicado: (2024)

Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges
por: Huang, Baixiang, et al.
Publicado: (2024)

Can Large Language Models Identify Authorship?
por: Huang, Baixiang, et al.
Publicado: (2024)

Privacy-Aware Decoding: Mitigating Privacy Leakage of Large Language Models in Retrieval-Augmented Generation
por: Wang, Haoran, et al.
Publicado: (2025)

DMamba: Decomposition-enhanced Mamba for Time Series Forecasting
por: Chen, Ruxuan, et al.
Publicado: (2026)

InfoMamba: An Attention-Free Hybrid Mamba-Transformer Model
por: Wang, Youjin, et al.
Publicado: (2026)

Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics
por: Zhang, Wenqing, et al.
Publicado: (2024)

DC-Mamber: A Dual Channel Prediction Model based on Mamba and Linear Transformer for Multivariate Time Series Forecasting
por: Fan, Bing, et al.
Publicado: (2025)

HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
por: Wang, Tan, et al.
Publicado: (2025)

Can LLM-Generated Misinformation Be Detected?
por: Chen, Canyu, et al.
Publicado: (2023)

AdaMamba: Adaptive Frequency-Gated Mamba for Long-Term Time Series Forecasting
por: Jiang, Xudong, et al.
Publicado: (2026)

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting
por: Zhao, Yanjun, et al.
Publicado: (2024)

Wavelet Mixture of Experts for Time Series Forecasting
por: Zhou, Zheng, et al.
Publicado: (2025)

Ister: Linear Transformer for Efficient Multivariate Time Series Forecasting
por: Cao, Fanpu, et al.
Publicado: (2024)

Sequential Order-Robust Mamba for Time Series Forecasting
por: Lee, Seunghan, et al.
Publicado: (2024)

Seg-MoE: Multi-Resolution Segment-wise Mixture-of-Experts for Time Series Forecasting Transformers
por: Ortigossa, Evandro S., et al.
Publicado: (2026)

Mamba or Transformer for Time Series Forecasting? Mixture of Universals (MoU) Is All You Need
por: Peng, Sijia, et al.
Publicado: (2024)

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting
por: Kong, Linghang, et al.
Publicado: (2024)

MillGNN: Learning Multi-Scale Lead-Lag Dependencies for Multi-Variate Time Series Forecasting
por: Wu, Binqing, et al.
Publicado: (2025)

Continuous Temporal Domain Generalization
por: Cai, Zekun, et al.
Publicado: (2024)

ISMRNN: An Implicitly Segmented RNN Method with Mamba for Long-Term Time Series Forecasting
por: Zhao, GaoXiang, et al.
Publicado: (2024)

DDT: A Dual-Masking Dual-Expert Transformer for Energy Time-Series Forecasting
por: Zhu, Mingnan, et al.
Publicado: (2026)

Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond
por: Ke, Yekun, et al.
Publicado: (2024)

Multi-Scale Dilated Convolution Network for Long-Term Time Series Forecasting
por: Li, Feifei, et al.
Publicado: (2024)

SEDformer: Event-Synchronous Spiking Transformers for Irregular Telemetry Time Series Forecasting
por: Zhou, Ziyu, et al.
Publicado: (2026)

STM3: Mixture of Multiscale Mamba for Long-Term Spatio-Temporal Time-Series Prediction
por: Chen, Haolong, et al.
Publicado: (2025)

DRFormer: Multi-Scale Transformer Utilizing Diverse Receptive Fields for Long Time-Series Forecasting
por: Ding, Ruixin, et al.
Publicado: (2024)

Online GPU Energy Optimization with Switching-Aware Bandits
por: Xu, Xiongxiao, et al.
Publicado: (2024)

TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting
por: Huang, Songtao, et al.
Publicado: (2025)

ASGMamba: Adaptive Spectral Gating Mamba for Multivariate Time Series Forecasting
por: Li, Qianyang, et al.
Publicado: (2026)

iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network
por: Liang, Ziran, et al.
Publicado: (2025)

Let Experts Feel Uncertainty: A Multi-Expert Label Distribution Approach to Probabilistic Time Series Forecasting
por: Zhou, Zhen, et al.
Publicado: (2026)