Cover Image

Decomposing the Time Series Forecasting Pipeline: A Modular Approach for Time Series Representation, Information Extraction, and Projection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Leppich, Robert, Stenger, Michael, Bauer, André, Kounev, Samuel
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

STEB: In Search of the Best Evaluation Approach for Synthetic Time Series
by: Stenger, Michael, et al.
Published: (2025)

TSRM: A Lightweight Temporal Feature Encoding Architecture for Time Series Forecasting and Imputation
by: Leppich, Robert, et al.
Published: (2025)

Time Series Representation Models
by: Leppich, Robert, et al.
Published: (2024)

Comprehensive Exploration of Synthetic Data Generation: A Survey
by: Bauer, André, et al.
Published: (2024)

TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
by: Wang, Shiyu, et al.
Published: (2024)

A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting
by: Caldas, Francisco, et al.
Published: (2026)

FMTK: A Modular Toolkit for Composable Time Series Foundation Model Pipelines
by: Shastri, Hetvi, et al.
Published: (2025)

Attention as Robust Representation for Time Series Forecasting
by: Niu, PeiSong, et al.
Published: (2024)

TSI: A Multi-View Representation Learning Approach for Time Series Forecasting
by: Gao, Wentao, et al.
Published: (2024)

OneCast: Structured Decomposition and Modular Generation for Cross-Domain Time Series Forecasting
by: Pan, Tingyue, et al.
Published: (2025)

A Unified Hyperparameter Optimization Pipeline for Transformer-Based Time Series Forecasting Models
by: Xu, Jingjing, et al.
Published: (2025)

An Adversarial Learning Approach to Irregular Time-Series Forecasting
by: Nam, Heejeong, et al.
Published: (2024)

Deconfounded Time Series Forecasting: A Causal Inference Approach
by: Gao, Wentao, et al.
Published: (2024)

Time Series Forecastability Measures
by: Wang, Rui, et al.
Published: (2025)

Ellipsoidal Time Series Forecasting
by: Wang, Qilin
Published: (2025)

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

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

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

Leveraging Multivariate Long-Term History Representation for Time Series Forecasting
by: Zhang, Huiliang, et al.
Published: (2025)

Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations
by: Naour, Etienne Le, et al.
Published: (2023)

TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting
by: Ankireddy, Sravan Kumar, et al.
Published: (2026)

DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting
by: Mysore, Naveen
Published: (2026)

Empowering Time Series Forecasting with LLM-Agents
by: Yeh, Chin-Chia Michael, et al.
Published: (2025)

Contrastive Time Series Forecasting with Anomalies
by: Ekstrand, Joel, et al.
Published: (2025)

Retrieval Augmented Time Series Forecasting
by: Tire, Kutay, et al.
Published: (2024)

Scaling Law for Time Series Forecasting
by: Shi, Jingzhe, et al.
Published: (2024)

Are General-Purpose Vision Models All We Need for 2D Medical Image Segmentation? A Cross-Dataset Empirical Study
by: Borst, Vanessa, et al.
Published: (2026)

Causal Time-Series Synchronization for Multi-Dimensional Forecasting
by: Mayr, Michael, et al.
Published: (2024)

LETS Forecast: Learning Embedology for Time Series Forecasting
by: Majeedi, Abrar, et al.
Published: (2025)

Multimodal Forecasting for Commodity Prices Using Spectrogram-Based and Time Series Representations
by: Park, Soyeon, et al.
Published: (2026)

ST-MTM: Masked Time Series Modeling with Seasonal-Trend Decomposition for Time Series Forecasting
by: Seo, Hyunwoo, 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)

CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
by: Koumar, Josef, et al.
Published: (2024)

Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
by: Zhou, Yitong, et al.
Published: (2025)

RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data
by: Yeh, Chin-Chia Michael, et al.
Published: (2024)

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

Inner-Instance Normalization for Time Series Forecasting
by: Jibao, Zipo, et al.
Published: (2025)

Time Series Forecasting Through the Lens of Dynamics
by: Brachet, Alexis-Raja, et al.
Published: (2025)

VARMA-Enhanced Transformer for Time Series Forecasting
by: Song, Jiajun, et al.
Published: (2025)

Nearest Neighbor Multivariate Time Series Forecasting
by: Zhang, Huiliang, et al.
Published: (2025)