:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Maru, Chihiro, Sato, Shoetsu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2506.02081
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection
by: Huang, Xiaoyu, et al.
Published: (2024)

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

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

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection
by: Khan, Uzair, et al.
Published: (2026)

Leveraging Time-Series Foundation Model for Subsurface Well Logs Prediction and Anomaly Detection
by: Koeshidayatullah, Ardiansyah, et al.
Published: (2024)

Forecast2Anomaly (F2A): Adapting Multivariate Time Series Foundation Models for Anomaly Prediction
by: Hassan, Atif, et al.
Published: (2025)

Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
by: Lan, Tian, et al.
Published: (2025)

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

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

Foundation Models for Anomaly Detection: Vision and Challenges
by: Ren, Jing, et al.
Published: (2025)

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

Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2025)

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

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

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

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

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

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)

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

Joint Selective State Space Model and Detrending for Robust Time Series Anomaly Detection
by: Chen, Junqi, et al.
Published: (2024)

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
by: Qiao, Hezhe, et al.
Published: (2025)

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

Foundation Models and Transformers for Anomaly Detection: A Survey
by: Ammar, Mouïn Ben, et al.
Published: (2025)

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

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

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

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

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)

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

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

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

Foundation Models for Time Series: A Survey
by: Kottapalli, Siva Rama Krishna, et al.
Published: (2025)

Transformers and Their Roles as Time Series Foundation Models
by: Wu, Dennis, et al.
Published: (2025)

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

Time Series Foundation Models for Process Model Forecasting
by: Yu, Yongbo, et al.
Published: (2025)

Labels Matter More Than Models: Rethinking the Unsupervised Paradigm in Time Series Anomaly Detection
by: Zhong, Zhijie, et al.
Published: (2025)