Image de couverture de livre

Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Nematirad, Reza, Pahwa, Anil, Natarajan, Balasubramaniam
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

SPDNet: Seasonal-Periodic Decomposition Network for Advanced Residential Demand Forecasting
par: Nematirad, Reza, et autres
Publié: (2025)

Are Data Embeddings effective in time series forecasting?
par: Nematirad, Reza, et autres
Publié: (2025)

DMamba: Decomposition-enhanced Mamba for Time Series Forecasting
par: Chen, Ruxuan, et autres
Publié: (2026)

Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting
par: Chi, Jinjin, et autres
Publié: (2026)

PESD-TSF: A Period-Aware and Explicit Structured Decomposition Framework for Long-Term Time Series Forecasting
par: Wang, Hua, et autres
Publié: (2026)

ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting
par: Seo, Hyunwoo, et autres
Publié: (2025)

A Decomposition Modeling Framework for Seasonal Time-Series Forecasting
par: Pang, Yining, et autres
Publié: (2024)

LMS-AutoTSF: Learnable Multi-Scale Decomposition and Integrated Autocorrelation for Time Series Forecasting
par: Delibasoglu, Ibrahim, et autres
Publié: (2024)

PeriodNet: Boosting the Potential of Attention Mechanism for Time Series Forecasting
par: Zhao, Bowen, et autres
Publié: (2025)

Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
par: Yang, Runze, et autres
Publié: (2025)

Routing Channel-Patch Dependencies in Time Series Forecasting with Graph Spectral Decomposition
par: Li, Dongyuan, et autres
Publié: (2026)

TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting
par: Huang, Songtao, et autres
Publié: (2025)

Epistemic Error Decomposition for Multi-step Time Series Forecasting: Rethinking Bias-Variance in Recursive and Direct Strategies
par: Green, Riku, et autres
Publié: (2025)

Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting
par: Fan, Wei, et autres
Publié: (2024)

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
par: Li, Zhe, et autres
Publié: (2023)

TimePerceiver: An Encoder-Decoder Framework for Generalized Time-Series Forecasting
par: Lee, Jaebin, et autres
Publié: (2025)

Causal Time-Series Synchronization for Multi-Dimensional Forecasting
par: Mayr, Michael, et autres
Publié: (2024)

A Unified Frequency Domain Decomposition Framework for Interpretable and Robust Time Series Forecasting
par: He, Cheng, et autres
Publié: (2025)

xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
par: Stitsyuk, Artyom, et autres
Publié: (2024)

Test Time Learning for Time Series Forecasting
par: Christou, Panayiotis, et autres
Publié: (2024)

Time Series Forecastability Measures
par: Wang, Rui, et autres
Publié: (2025)

Ellipsoidal Time Series Forecasting
par: Wang, Qilin
Publié: (2025)

Performative Time-Series Forecasting
par: Zhao, Zhiyuan, et autres
Publié: (2023)

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
par: Wang, Hao, et autres
Publié: (2025)

Forecasting Time Series with LLMs via Patch-Based Prompting and Decomposition
par: Bumb, Mayank, et autres
Publié: (2025)

Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting
par: Li, Jinglin, et autres
Publié: (2026)

PENGUIN: Enhancing Transformer with Periodic-Nested Group Attention for Long-term Time Series Forecasting
par: Sun, Tian, et autres
Publié: (2025)

VarDrop: Enhancing Training Efficiency by Reducing Variate Redundancy in Periodic Time Series Forecasting
par: Kang, Junhyeok, et autres
Publié: (2025)

DSAT-HD: Dual-Stream Adaptive Transformer with Hybrid Decomposition for Multivariate Time Series Forecasting
par: Wang, Zixu, et autres
Publié: (2025)

A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
par: Zhong, Shuhan, et autres
Publié: (2023)

Numerion: A Multi-Hypercomplex Model for Time Series Forecasting
par: Cao, Hanzhong, et autres
Publié: (2025)

ms-Mamba: Multi-scale Mamba for Time-Series Forecasting
par: Karadag, Yusuf Meric, et autres
Publié: (2025)

Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting
par: Green, Riku, et autres
Publié: (2024)

SeriesGAN: Time Series Generation via Adversarial and Autoregressive Learning
par: EskandariNasab, MohammadReza, et autres
Publié: (2024)

Interpretable Time Series Autoregression for Periodicity Quantification
par: Chen, Xinyu, et autres
Publié: (2025)

Semi-Periodic Activation for Time Series Classification
par: Júnior, José Gilberto Barbosa de Medeiros, et autres
Publié: (2024)

LETS Forecast: Learning Embedology for Time Series Forecasting
par: Majeedi, Abrar, et autres
Publié: (2025)

Contrastive Time Series Forecasting with Anomalies
par: Ekstrand, Joel, et autres
Publié: (2025)

Retrieval Augmented Time Series Forecasting
par: Tire, Kutay, et autres
Publié: (2024)

Scaling Law for Time Series Forecasting
par: Shi, Jingzhe, et autres
Publié: (2024)