Image de couverture de livre

Delving into Non-Exchangeability for Conformal Prediction in Graph-Structured Multivariate Time Series

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Guo, Ruichao, Han, Xingyao, Wenshui, Luo, Liu, Zhe, Gong, Chen, Wang, Hesheng
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Online Conformal Prediction for Non-Exchangeable Panel Data
par: Tu, Daohong, et autres
Publié: (2026)

Non-Exchangeable Conformal Risk Control
par: Farinhas, António, et autres
Publié: (2023)

Non-Exchangeable Conformal Language Generation with Nearest Neighbors
par: Ulmer, Dennis, et autres
Publié: (2024)

Transformer Conformal Prediction for Time Series
par: Lee, Junghwan, et autres
Publié: (2024)

Are KANs Effective for Multivariate Time Series Forecasting?
par: Han, Xiao, et autres
Publié: (2024)

Graph-Aware Contrasting for Multivariate Time-Series Classification
par: Wang, Yucheng, et autres
Publié: (2023)

SCFormer: Structured Channel-wise Transformer with Cumulative Historical State for Multivariate Time Series Forecasting
par: Guo, Shiwei, et autres
Publié: (2025)

Adapformer: Adaptive Channel Management for Multivariate Time Series Forecasting
par: Luo, Yuchen, et autres
Publié: (2025)

SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion
par: Han, Lu, et autres
Publié: (2024)

Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data
par: Wang, Yucheng, et autres
Publié: (2023)

Spatio-temporal Multivariate Time Series Forecast with Chosen Variables
par: Liu, Zibo, et autres
Publié: (2025)

Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis
par: Liu, Zhe, et autres
Publié: (2024)

CoCAI: Copula-based Conformal Anomaly Identification for Multivariate Time-Series
par: Pearson, Nicholas A., et autres
Publié: (2025)

One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
par: Gao, Mengzhou, et autres
Publié: (2026)

ForecastGrapher: Redefining Multivariate Time Series Forecasting with Graph Neural Networks
par: Cai, Wanlin, et autres
Publié: (2024)

ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting
par: Liu, Xvyuan, et autres
Publié: (2025)

Prospective Multi-Graph Cohesion for Multivariate Time Series Anomaly Detection
par: Chen, Jiazhen, et autres
Publié: (2025)

DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting
par: Liu, Qinshuo, et autres
Publié: (2024)

Benchmarking Graph Representations and Graph Neural Networks for Multivariate Time Series Classification
par: Yang, Wennuo, et autres
Publié: (2025)

Flow-based Conformal Prediction for Multi-dimensional Time Series
par: Lee, Junghwan, et autres
Publié: (2025)

MCformer: Multivariate Time Series Forecasting with Mixed-Channels Transformer
par: Han, Wenyong, et autres
Publié: (2024)

TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification
par: Liu, Huaiyuan, et autres
Publié: (2023)

Algorithmic Recourse in Abnormal Multivariate Time Series
par: Han, Xiao, et autres
Publié: (2023)

TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting
par: Hu, Jiaxi, et autres
Publié: (2024)

Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
par: Pan, Yiyuan, et autres
Publié: (2025)

Periodic Graph-Enhanced Multivariate Time Series Anomaly Detector
par: Li, Jia, et autres
Publié: (2025)

Channel Matters: Estimating Channel Influence for Multivariate Time Series
par: Wang, Muyao, et autres
Publié: (2024)

GRAPHLCP: Structure-Aware Localized Conformal Prediction on Graphs
par: Baghershahi, Peyman, et autres
Publié: (2026)

Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
par: Cho, Dongchan, et autres
Publié: (2025)

Conformal Inference for Time Series over Graphs
par: Dua, Sonakshi, et autres
Publié: (2025)

Multivariate Conformal Prediction using Optimal Transport
par: Klein, Michal, et autres
Publié: (2025)

Structural Knowledge Informed Continual Multivariate Time Series Forecasting
par: Pan, Zijie, et autres
Publié: (2024)

Label-Free Multivariate Time Series Anomaly Detection
par: Zhou, Qihang, et autres
Publié: (2023)

Conformal Load Prediction with Transductive Graph Autoencoders
par: Luo, Rui, et autres
Publié: (2024)

Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
par: Reizinger, Patrik, et autres
Publié: (2024)

Learning Recursive Multi-Scale Representations for Irregular Multivariate Time Series Forecasting
par: Li, Boyuan, et autres
Publié: (2026)

Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering
par: Tan, Zexi, et autres
Publié: (2025)

SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
par: Jiang, Yue, et autres
Publié: (2024)

Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time Series
par: Liu, Mingzhu, et autres
Publié: (2024)

Kernel-based Optimally Weighted Conformal Time-Series Prediction
par: Lee, Jonghyeok, et autres
Publié: (2024)