Cover Image

Bridging the Last Mile of Prediction: Enhancing Time Series Forecasting with Conditional Guided Flow Matching

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Huibo, Yu, Runlong, Wu, Likang, Wang, Xianquan, Liu, Qi
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

NeuTSFlow: Modeling Continuous Functions Behind Time Series Forecasting
by: Xu, Huibo, et al.
Published: (2025)

Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
by: Zhang, Jintao, et al.
Published: (2025)

StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser
by: Zhang, Jintao, et al.
Published: (2026)

Bridging the Last Mile of Time Series Forecasting with LLM Agents
by: Liao, Yuhua, et al.
Published: (2026)

PrismFlow: Residual Dynamics for Flow Matching in Time-Series Generation
by: Zhang, Junru, et al.
Published: (2026)

Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
by: Kollovieh, Marcel, et al.
Published: (2024)

CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting
by: Pan, Bokai, et al.
Published: (2026)

MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
by: Tao, Xiaoyu, et al.
Published: (2026)

Semantically-Guided Inference for Conditional Diffusion Models: Enhancing Covariate Consistency in Time Series Forecasting
by: Ding, Rui, et al.
Published: (2025)

Path-Guided Flow Matching for Dataset Distillation
by: Li, Xuhui, et al.
Published: (2026)

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

Abnormality Forecasting: Time Series Anomaly Prediction via Future Context Modeling
by: Zhao, Sinong, et al.
Published: (2024)

Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting
by: Hu, Yifan, 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)

Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability
by: Xu, Kunpeng, et al.
Published: (2024)

A Bi-Objective Approach to Last-Mile Delivery Routing Considering Driver Preferences
by: Mesa, Juan Pablo, et al.
Published: (2024)

Trajectory Flow Matching with Applications to Clinical Time Series Modeling
by: Zhang, Xi, et al.
Published: (2024)

Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
by: Li, Zhe, et al.
Published: (2023)

FlowState: Sampling Rate Invariant Time Series Forecasting
by: Graf, Lars, et al.
Published: (2025)

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

STELLA: Guiding Large Language Models for Time Series Forecasting with Semantic Abstractions
by: Fan, Junjie, et al.
Published: (2025)

Nested Spatio-Temporal Time Series Forecasting
by: Ai, Yinghao, et al.
Published: (2026)

Revisiting Attention for Multivariate Time Series Forecasting
by: Wu, Haixiang
Published: (2024)

Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization
by: Gong, Peiliang, et al.
Published: (2025)

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

Operator Flow Matching for Timeseries Forecasting
by: Lee, Yolanne Yi Ran, et al.
Published: (2025)

IndexNet: Timestamp and Variable-Aware Modeling for Time Series Forecasting
by: Wu, Beiliang, et al.
Published: (2025)

Are KANs Effective for Multivariate Time Series Forecasting?
by: Han, Xiao, et al.
Published: (2024)

FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting
by: Yue, Wenzhen, et al.
Published: (2025)

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

Role-Aware Conditional Inference for Spatiotemporal Ecosystem Carbon Flux Prediction
by: Sun, Yiming, et al.
Published: (2026)

TimeSAF: Towards LLM-Guided Semantic Asynchronous Fusion for Time Series Forecasting
by: Zhang, Fan, et al.
Published: (2026)

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

Enhancing Time Series Forecasting via Logic-Inspired Regularization
by: Zhang, Jianqi, et al.
Published: (2025)

Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
by: Cao, Fanpu, et al.
Published: (2026)

TimeCNN: Refining Cross-Variable Interaction on Time Point for Time Series Forecasting
by: Hu, Ao, et al.
Published: (2024)

Space Group Conditional Flow Matching
by: Puny, Omri, et al.
Published: (2025)

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

Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection
by: Baumgartner, David, et al.
Published: (2026)

Deep Coupling Network For Multivariate Time Series Forecasting
by: Yi, Kun, et al.
Published: (2024)