Cover Image

FAF: A Feature-Adaptive Framework for Few-Shot Time Series Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ouyang, Pengpeng, Chen, Dong, Yang, Tong, Feng, Shuo, Jin, Zhao, Xu, Mingliang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FaultDiffusion: Few-Shot Fault Time Series Generation with Diffusion Model
by: Xu, Yi, et al.
Published: (2025)

In-Context and Few-Shots Learning for Forecasting Time Series Data based on Large Language Models
by: Gopali, Saroj, et al.
Published: (2025)

SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting
by: Huang, Ting-Ji, et al.
Published: (2025)

Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
by: Ekambaram, Vijay, et al.
Published: (2024)

A Survey of Few-Shot Learning for Biomedical Time Series
by: Li, Chenqi, et al.
Published: (2024)

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
by: Liu, Zhining, et al.
Published: (2025)

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

StretchTime: Adaptive Time Series Forecasting via Symplectic Attention
by: Kim, Yubin, et al.
Published: (2026)

The Forecast After the Forecast: A Post-Processing Shift in Time Series
by: Liang, Daojun, et al.
Published: (2026)

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)

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

Deciphering Invariant Feature Decoupling in Source-free Time Series Forecasting with Proxy Denoising
by: Yan, Kangjia, et al.
Published: (2025)

Optimal Look-back Horizon for Time Series Forecasting in Federated Learning
by: Tang, Dahao, et al.
Published: (2025)

Large Language Models are Few-shot Multivariate Time Series Classifiers
by: Chen, Yakun, et al.
Published: (2025)

Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting
by: Madarasingha, Chamara, et al.
Published: (2025)

EffiCANet: Efficient Time Series Forecasting with Convolutional Attention
by: Zhou, Xinxing, et al.
Published: (2024)

Adaptive Information Routing for Multimodal Time Series Forecasting
by: Seo, Jun, et al.
Published: (2025)

A Scalable and Transferable Time Series Prediction Framework for Demand Forecasting
by: Park, Young-Jin, et al.
Published: (2024)

DSAT-HD: Dual-Stream Adaptive Transformer with Hybrid Decomposition for Multivariate Time Series Forecasting
by: Wang, Zixu, et al.
Published: (2025)

Global Feature Enhancing and Fusion Framework for Strain Gauge Time Series Classification
by: Zhang, Xu, et al.
Published: (2025)

Performative Time-Series Forecasting
by: Zhao, Zhiyuan, et al.
Published: (2023)

EventTSF: Event-Aware Non-Stationary Time Series Forecasting
by: Ge, Yunfeng, et al.
Published: (2025)

FEATHer: Fourier-Efficient Adaptive Temporal Hierarchy Forecaster for Time-Series Forecasting
by: Lee, Jaehoon, et al.
Published: (2026)

Context Matters: Leveraging Contextual Features for Time Series Forecasting
by: Chattopadhyay, Sameep, et al.
Published: (2024)

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
by: Yang, Runze, et al.
Published: (2025)

OLMA: One Loss for More Accurate Time Series Forecasting
by: Shi, Tianyi, et al.
Published: (2025)

CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables
by: Lu, Jiecheng, et al.
Published: (2024)

MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMs
by: Chatzigeorgakidis, Georgios, et al.
Published: (2024)

HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
by: Yang, Haonan, et al.
Published: (2025)

Test Time Learning for Time Series Forecasting
by: Christou, Panayiotis, et al.
Published: (2024)

SVTime: Small Time Series Forecasting Models Informed by "Physics" of Large Vision Model Forecasters
by: Shen, ChengAo, et al.
Published: (2025)

Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
by: Yang, Linxiao, et al.
Published: (2026)

Adapformer: Adaptive Channel Management for Multivariate Time Series Forecasting
by: Luo, Yuchen, et al.
Published: (2025)

Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
by: Ye, Weiwei, et al.
Published: (2024)

Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting
by: Zhang, Xiao, et al.
Published: (2026)

BEAT: Balanced Frequency Adaptive Tuning for Long-Term Time-Series Forecasting
by: Li, Zhixuan, et al.
Published: (2025)

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

DeepBooTS: Dual-Stream Residual Boosting for Drift-Resilient Time-Series Forecasting
by: Liang, Daojun, et al.
Published: (2025)

TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)