CATS: Mitigating Correlation Shift for Multivariate Time Series Classification
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Xiao, Zeng, Zhichen, Wei, Tianxin, Liu, Zhining, chen, Yuzhong, Tong, Hanghang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
by: Lin, Xiao, et al.
Published: (2024)
by: Lin, Xiao, et al.
Published: (2024)
AIM: Attributing, Interpreting, Mitigating Data Unfairness
by: Liu, Zhining, et al.
Published: (2024)
by: Liu, Zhining, et al.
Published: (2024)
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
by: Liu, Zhining, et al.
Published: (2025)
by: Liu, Zhining, et al.
Published: (2025)
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
by: Bao, Wenxuan, et al.
Published: (2024)
by: Bao, Wenxuan, et al.
Published: (2024)
ALERT: Zero-shot LLM Jailbreak Detection via Internal Discrepancy Amplification
by: Lin, Xiao, et al.
Published: (2026)
by: Lin, Xiao, et al.
Published: (2026)
Hierarchical Multi-Marginal Optimal Transport for Network Alignment
by: Zeng, Zhichen, et al.
Published: (2023)
by: Zeng, Zhichen, et al.
Published: (2023)
Flow Matching Meets Biology and Life Science: A Survey
by: Li, Zihao, et al.
Published: (2025)
by: Li, Zihao, 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)
by: Lu, Jiecheng, et al.
Published: (2024)
CATS-Linear: Classification Auxiliary Linear Model for Time Series Forecasting
by: Jibao, Zipo, et al.
Published: (2025)
by: Jibao, Zipo, et al.
Published: (2025)
Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025)
by: Zeng, Zhichen, et al.
Published: (2025)
Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative
by: Li, Zihao, et al.
Published: (2025)
by: Li, Zihao, et al.
Published: (2025)
Causal and Local Correlations Based Network for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)
by: Liu, Zhining, et al.
Published: (2025)
Class-Imbalanced Graph Learning without Class Rebalancing
by: Liu, Zhining, et al.
Published: (2023)
by: Liu, Zhining, et al.
Published: (2023)
ST-Tree with Interpretability for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
PyG-SSL: A Graph Self-Supervised Learning Toolkit
by: Zheng, Lecheng, et al.
Published: (2024)
by: Zheng, Lecheng, et al.
Published: (2024)
Neural Predictive Control to Coordinate Discrete- and Continuous-Time Models for Time-Series Analysis with Control-Theoretical Improvements
by: Li, Haoran, et al.
Published: (2025)
by: Li, Haoran, et al.
Published: (2025)
Saffron-1: Safety Inference Scaling
by: Qiu, Ruizhong, et al.
Published: (2025)
by: Qiu, Ruizhong, et al.
Published: (2025)
E2USD: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series
by: Lai, Zhichen, et al.
Published: (2024)
by: Lai, Zhichen, et al.
Published: (2024)
VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting
by: Yang, Yingnan, et al.
Published: (2024)
by: Yang, Yingnan, et al.
Published: (2024)
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
by: Le, Xuan-May, et al.
Published: (2024)
by: Le, Xuan-May, et al.
Published: (2024)
TSAQA: Time Series Analysis Question And Answering Benchmark
by: Jing, Baoyu, et al.
Published: (2026)
by: Jing, Baoyu, et al.
Published: (2026)
Contrast Similarity-Aware Dual-Pathway Mamba for Multivariate Time Series Node Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
Spatio-temporal Multivariate Time Series Forecast with Chosen Variables
by: Liu, Zibo, et al.
Published: (2025)
by: Liu, Zibo, et al.
Published: (2025)
Joint Optimal Transport and Embedding for Network Alignment
by: Yu, Qi, et al.
Published: (2025)
by: Yu, Qi, et al.
Published: (2025)
Are KANs Effective for Multivariate Time Series Forecasting?
by: Han, Xiao, et al.
Published: (2024)
by: Han, Xiao, et al.
Published: (2024)
CANDI: Curated Test-Time Adaptation for Multivariate Time-Series Anomaly Detection Under Distribution Shift
by: Kim, HyunGi, et al.
Published: (2026)
by: Kim, HyunGi, et al.
Published: (2026)
Meta-learning to Address Data Shift in Time Series Classification
by: Myren, Samuel, et al.
Published: (2026)
by: Myren, Samuel, et al.
Published: (2026)
HTMformer: Hybrid Time and Multivariate Transformer for Time Series Forecasting
by: Wang, Tan, et al.
Published: (2025)
by: Wang, Tan, et al.
Published: (2025)
Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series
by: Song, Xianhao, et al.
Published: (2026)
by: Song, Xianhao, et al.
Published: (2026)
SDGF: Fusing Static and Multi-Scale Dynamic Correlations for Multivariate Time Series Forecasting
by: Wang, Shaoxun, et al.
Published: (2025)
by: Wang, Shaoxun, et al.
Published: (2025)
VSFormer: Value and Shape-Aware Transformer with Prior-Enhanced Self-Attention for Multivariate Time Series Classification
by: Xi, Wenjie, et al.
Published: (2024)
by: Xi, Wenjie, et al.
Published: (2024)
Exploring Spiking Neural Networks for Binary Classification in Multivariate Time Series at the Edge
by: Ghawaly, James, et al.
Published: (2025)
by: Ghawaly, James, et al.
Published: (2025)
Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering
by: Niu, Yiming, et al.
Published: (2025)
by: Niu, Yiming, et al.
Published: (2025)
TimeDRL: Disentangled Representation Learning for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2023)
by: Chang, Ching, et al.
Published: (2023)
Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
by: Gao, Mengzhou, et al.
Published: (2026)
by: Gao, Mengzhou, et al.
Published: (2026)
SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence
by: Liu, Zhining, et al.
Published: (2025)
by: Liu, Zhining, et al.
Published: (2025)
HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)
by: Feng, Shibo, et al.
Published: (2025)
Anomalous Agreement: How to find the Ideal Number of Anomaly Classes in Correlated, Multivariate Time Series Data
by: Rewicki, Ferdinand, et al.
Published: (2025)
by: Rewicki, Ferdinand, et al.
Published: (2025)
Similar Items
-
BACKTIME: Backdoor Attacks on Multivariate Time Series Forecasting
by: Lin, Xiao, et al.
Published: (2024) -
AIM: Attributing, Interpreting, Mitigating Data Unfairness
by: Liu, Zhining, et al.
Published: (2024) -
Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
by: Liu, Zhining, et al.
Published: (2025) -
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
by: Bao, Wenxuan, et al.
Published: (2024) -
ALERT: Zero-shot LLM Jailbreak Detection via Internal Discrepancy Amplification
by: Lin, Xiao, et al.
Published: (2026)