Cover Image

Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Qiu, Xiangfei, Yan, Kangjia, Liu, Xvyuan, Wu, Xingjian, Hu, Jilin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting
by: Liu, Xvyuan, et al.
Published: (2025)

Rethinking Irregular Time Series Forecasting: A Simple yet Effective Baseline
by: Liu, Xvyuan, et al.
Published: (2025)

DBLoss: Decomposition-based Loss Function for Time Series Forecasting
by: Qiu, Xiangfei, et al.
Published: (2025)

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
by: Qiu, Xiangfei, et al.
Published: (2024)

SEER: Transformer-based Robust Time Series Forecasting via Automated Patch Enhancement and Replacement
by: Qiu, Xiangfei, et al.
Published: (2026)

DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables
by: Qiu, Xiangfei, et al.
Published: (2025)

A Comprehensive Survey of Deep Learning for Multivariate Time Series Forecasting: A Channel Strategy Perspective
by: Qiu, Xiangfei, et al.
Published: (2025)

FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
by: Wu, Xingjian, et al.
Published: (2025)

Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
by: Wu, Xingjian, et al.
Published: (2025)

$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting
by: Wu, Xingjian, et al.
Published: (2025)

GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
by: Li, Zhengyu, et al.
Published: (2026)

Task-Aware Mixture-of-Experts for Time Series Analysis
by: Wu, Xingjian, et al.
Published: (2025)

CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching
by: Wu, Xingjian, et al.
Published: (2024)

TimeART: Towards Agentic Time Series Reasoning via Tool-Augmentation
by: Wu, Xingjian, et al.
Published: (2026)

EasyTime: Time Series Forecasting Made Easy
by: Qiu, Xiangfei, et al.
Published: (2024)

Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
by: Qiu, Xiangfei, et al.
Published: (2025)

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast
by: Hu, Shiyan, et al.
Published: (2024)

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
by: Qiu, Xiangfei, et al.
Published: (2024)

Probabilistic Circuits for Irregular Multivariate Time Series Forecasting
by: Klötergens, Christian, et al.
Published: (2026)

Revitalizing Canonical Pre-Alignment for Irregular Multivariate Time Series Forecasting
by: Zhou, Ziyu, et al.
Published: (2025)

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting
by: Rezaei, Mohammad R., et al.
Published: (2026)

TSFM-Bench: A Comprehensive and Unified Benchmark of Foundation Models for Time Series Forecasting
by: Li, Zhe, et al.
Published: (2024)

SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation
by: Gao, Hongfan, et al.
Published: (2024)

Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
by: Li, Boyuan, et al.
Published: (2026)

TAB: Unified Benchmarking of Time Series Anomaly Detection Methods
by: Qiu, Xiangfei, et al.
Published: (2025)

STRGCN: Capturing Asynchronous Spatio-Temporal Dependencies for Irregular Multivariate Time Series Forecasting
by: Wang, Yulong, et al.
Published: (2025)

Unlocking the Potential of Linear Networks for Irregular Multivariate Time Series Forecasting
by: Wang, Chengsen, et al.
Published: (2025)

HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
by: Li, Boyuan, et al.
Published: (2025)

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
by: Wu, Xingjian, et al.
Published: (2026)

Probabilistic Learning of Multivariate Time Series with Temporal Irregularity
by: Li, Yijun, et al.
Published: (2023)

Mixing It Up: Exploring Mixer Networks for Irregular Multivariate Time Series Forecasting
by: Klötergens, Christian, et al.
Published: (2025)

FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series Forecasting
by: Wang, Yulong, et al.
Published: (2025)

Valid and Expressive Copulas for Irregular Multivariate Time Series
by: Klötergens, Christian, et al.
Published: (2026)

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

A Statistical Approach for Modeling Irregular Multivariate Time Series with Missing Observations
by: Nie, Dingyi, et al.
Published: (2026)

Temporal Query Network for Efficient Multivariate Time Series Forecasting
by: Lin, Shengsheng, et al.
Published: (2025)

FAiT: Frequency-Aware Inverted Transformer for Multivariate Time Series Forecasting
by: He, Peng, et al.
Published: (2026)

LightGTS-Cov: Covariate-Enhanced Time Series Forecasting
by: Shang, Yong, et al.
Published: (2026)

TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series Analysis
by: Liu, Jiexi, et al.
Published: (2024)

Physiome-ODE: A Benchmark for Irregularly Sampled Multivariate Time Series Forecasting Based on Biological ODEs
by: Klötergens, Christian, et al.
Published: (2025)