:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Zhou, Haokun
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2601.21050
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Correlating Time Series with Interpretable Convolutional Kernels
by: Chen, Xinyu, et al.
Published: (2024)

Federated Quantum Kernel Learning for Anomaly Detection in Multivariate IoT Time-Series
by: Chen, Kuan-Cheng, et al.
Published: (2025)

Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
by: Tang, Qideng, et al.
Published: (2026)

Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection
by: Zhang, Ruyi, et al.
Published: (2024)

VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting
by: Yang, Yingnan, et al.
Published: (2024)

IMPACT: Influence Modeling for Open-Set Time Series Anomaly Detection
by: Zhou, Xiaohui, et al.
Published: (2026)

CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables
by: Zhou, Pengfei, et al.
Published: (2025)

PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection
by: Park, Jinju, et al.
Published: (2026)

A Problem-Oriented Taxonomy of Evaluation Metrics for Time Series Anomaly Detection
by: Yang, Kaixiang, et al.
Published: (2025)

Large Language Model Guided Knowledge Distillation for Time Series Anomaly Detection
by: Liu, Chen, et al.
Published: (2024)

mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
by: Zhou, Xiaona, et al.
Published: (2025)

Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection
by: Chen, Yutong, et al.
Published: (2024)

Adaptive Conformal Anomaly Detection with Time Series Foundation Models for Signal Monitoring
by: Gil, Natalia Martinez, et al.
Published: (2026)

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

Learning Unified Representations of Normalcy for Time Series Anomaly Detection
by: Sarker, Prithul, et al.
Published: (2026)

Time Series Foundational Models: Their Role in Anomaly Detection and Prediction
by: Shyalika, Chathurangi, et al.
Published: (2024)

Deep Learning for Time Series Anomaly Detection: A Survey
by: Darban, Zahra Zamanzadeh, et al.
Published: (2022)

An Improved Time Series Anomaly Detection by Applying Structural Similarity
by: Wang, Tiejun, et al.
Published: (2025)

Towards Foundation Auto-Encoders for Time-Series Anomaly Detection
by: González, Gastón García, et al.
Published: (2025)

CCE: Confidence-Consistency Evaluation for Time Series Anomaly Detection
by: Zhong, Zhijie, et al.
Published: (2025)

ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN
by: Bashar, Md Abul, et al.
Published: (2023)

Matrix Profile for Anomaly Detection on Multidimensional Time Series
by: Yeh, Chin-Chia Michael, et al.
Published: (2024)

CAPMix: Robust Time Series Anomaly Detection Based on Abnormal Assumptions with Dual-Space Mixup
by: Mou, Xudong, et al.
Published: (2025)

Efficient Representations for High-Cardinality Categorical Variables in Machine Learning
by: Liang, Zixuan
Published: (2025)

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection
by: Özer, Kadir-Kaan, et al.
Published: (2026)

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

VACE: Learning Geometrically Structured Representations for Time Series Anomaly Detection
by: Cencillo, Alberto D., et al.
Published: (2026)

Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
by: Cho, Dongchan, et al.
Published: (2025)

From Chaos to Clarity: Time Series Anomaly Detection in Astronomical Observations
by: Hao, Xinli, et al.
Published: (2024)

Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection
by: Xu, Hongzuo, et al.
Published: (2022)

RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection
by: Maru, Chihiro, et al.
Published: (2025)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)

Active Learning and Transfer Learning for Anomaly Detection in Time-Series Data
by: Kelleher, John D., et al.
Published: (2025)

Leveraging Intermediate Representations of Time Series Foundation Models for Anomaly Detection
by: Han, Chan Sik, et al.
Published: (2025)

Causal Disentanglement Learning for Accurate Anomaly Detection in Multivariate Time Series
by: Kim, Wonah, et al.
Published: (2025)

Dive into Time-Series Anomaly Detection: A Decade Review
by: Boniol, Paul, et al.
Published: (2024)

An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework
by: Ghanim, Jihan, et al.
Published: (2024)

Contrastive Time Series Forecasting with Anomalies
by: Ekstrand, Joel, 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)

Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection
by: Özer, Kadir-Kaan, et al.
Published: (2026)