Unsupervised Anomaly Detection

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Overview

Unsupervised anomaly detection learns what typical data look like, then flags samples or events that depart from those patterns when anomaly labels are unavailable. Methods include density and distance scoring, such as Isolation Forest and k-nearest neighbors; one-class models; reconstruction and forecasting; and self-supervised or generative models that learn useful representations of normal data. For time series, graphs, images, audio, and multiple sensor modalities, methods can also model temporal, relational, spatial, or cross-modal structure, supporting applications from industrial inspection and medical imaging to network security and scientific monitoring. A central challenge is reliable deployment: contamination of training data, shifts in normal behavior, and threshold choices can undermine performance, while strong results on curated benchmarks may not transfer across domains.

Latest papers

CardsList

229 papers29 papers in the last four weeks, up 26% on the four weeks before. 0.2% of all new papers.

  1. Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection

    Feb 25, 2026Dhiraj Neupane, Richard Dazeley, Mohamed Reda Bouadjenek +1Fault DetectionUnsupervised Anomaly Detection

    Deakin University Waurn Ponds, Victoria, Australia

  2. Inspectorch: Efficient rare event exploration in solar observations

    Feb 23, 2026C. J. Díaz Baso, I. J. Soler Poquet, C. Kuckein +2Solar PhysicsAnomaly Detection

    Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, N-0315 Oslo, Norway · Rosseland Centre for Solar Physics, University of Oslo, P.O. Box 1029 Blindern, N-0315 Oslo, Norway · Instituto de Astrofísica de Canarias, C/Vía Láctea s/n, E-38205 La Laguna, Tenerife, Spain +3

  3. Unsupervised Anomaly Detection in NSL-KDD Using ββ-VAE: A Latent Space and Reconstruction Error Approach

    Feb 23, 2026Dylan Baptiste, Ramla Saddem, Alexandre Philippot +1Unsupervised Anomaly DetectionNetwork Intrusion Detection

    CRESTIC · Université de Reims Champagne-Ardenne, CRESTIC, Reims, France · Seckiot, Paris, France

  4. RAID: Retrieval-Augmented Anomaly Detection

    Feb 23, 2026Mingxiu Cai, Zhe Zhang, Gaochang Wu +2Unsupervised Anomaly DetectionAnomaly Detection

    State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University · University of Surrey

  5. TimeRadar: A Domain-Rotatable Foundation Model for Time Series Anomaly Detection

    Feb 22, 2026Hui He, Hezhe Qiao, Yutong Chen +2Time-Series Anomaly DetectionUnsupervised Anomaly Detection

    School of Computing and Information Systems, Singapore Management University, Singapore · Chongqing Institute of Green and Intelligent Technology, University of Chinese Academy of Sciences, Chongqing, China · State Information Center, Beijing, China

  6. Mind the Gap: Detecting Cluster Exits for Robust Local Density-Based Score Normalization in Anomalous Sound Detection

    Feb 21, 2026Kevin Wilkinghoff, Gordon Wichern, Jonathan Le Roux +1Anomaly DetectionUnsupervised Anomaly Detection

    Department of Electronic Systems, Aalborg University, Aalborg, Denmark · Pioneer Centre for Artificial Intelligence, Copenhagen, Denmark · Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA

  7. Conditional Flow Matching for Continuous Anomaly Detection in Autonomous Driving on a Manifold-Aware Spectral Space

    Feb 19, 2026Antonio Guillen-PerezUnsupervised Anomaly DetectionAutonomous Driving Safety Evaluation

    Independent Researcher

  8. StructCore: Structure-Aware Image-Level Scoring for Training-Free Unsupervised Anomaly Detection

    Feb 19, 2026Joongwon Chae, Lihui Luo, Yang Liu +8Unsupervised Anomaly DetectionAnomaly Detection

    Tsinghua University Shenzhen International Graduate School, Shenzhen, China · Ratel Soft · Affiliated Fifth Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China +1

  9. Forecasting Anomaly Precursors via Uncertainty-Aware Time-Series Ensembles

    Feb 19, 2026Hyeongwon Kang, Jinwoo Park, Seunghun Han +1Early Warning DetectionTime-Series Anomaly Detection

    Department of Industrial & Management Engineering, Korea University, 126-16 Anam-dong 5-ga, Seongbuk-gu, Seoul, Republic of Korea · Department of Industrial Engineering, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul, Republic of Korea · LG CNS, 71, Magokjungang 8-ro, Gangseo-gu, Seoul, Republic of Korea

  10. LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection

    Feb 9, 2026Dezheng Wang, Tong Chen, Guansong Pang +3Multi-View LearningUnsupervised Anomaly Detection

    School of Automation, Southeast University Nanjing, China · School of Electrical Engineering and Computer Science, The University of Queensland Brisbane, Australia · School of Computing and Information Systems, Singapore Management University Singapore

  11. Auditing Frozen-Encoder Anomaly Detection Across Mechanical Systems: Representation Provenance, Calibration, and Protocol Effects

    Jan 16, 2026Jose Sánchez AndreuMahalanobis DistanceIndustrial Anomaly Detection

    Independent Researcher, Murcia, Spain

  12. Explainable Visual Anomaly Detection via Concept Bottleneck Models

    Nov 25, 2025Arianna Stropeni, Valentina Zaccaria, Francesco Borsatti +3Interpretable Anomaly DetectionAnomaly Localization

    University of Padova, Italy

  13. Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection

    Oct 18, 2025Dongchan Cho, Jiho Han, Keumyeong Kang +3Time-Series Anomaly DetectionUnsupervised Anomaly Detection

    Industrial AI Lab, SimPlatform Co. Ltd. Affiliate Research Institute

  14. Isolation-based Spherical Ensemble Representations for Tabular Anomaly Detection

    Oct 15, 2025Yang Cao, Sikun Yang, Hao Tian +5Tabular Anomaly DetectionIsolation Forest

    Tsinghua Shenzhen International Graduate School, Tsinghua University, China · School of Computing and Information Technology, Great Bay University, China · School of Compuer Science, Nanjing University, China +3

  15. OCSVM-Guided Representation Learning for Unsupervised Anomaly Detection

    Jul 25, 2025Nicolas Pinon, Robin Trombetta, Carole LartizienMedical Image Anomaly DetectionUnsupervised Representation Learning

    MYRIAD

  16. Detecting and explaining clinical-omics inconsistencies to improve patient cohort stratification: an application to Parkinson's disease

    Jul 4, 2025José A. Pardo-Pérez, Tomás Bernal, Jaime Ñiguez +5Medical DiagnosisUnsupervised Anomaly Detection

    Department of Information and Communications Engineering, Faculty of Computer Science, University of Murcia, Murcia, Spain. · Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK. · Department of Neurology, Washington University School of Medicine, Saint Louis, MO, 63110, USA. +1

  17. ISP-AD: A Large-Scale Real-World Dataset for Advancing Industrial Anomaly Detection with Synthetic and Real Defects

    Mar 6, 2025Paul J. Krassnig, Dieter P. GruberIndustrial Anomaly DetectionIndustrial Inspection

    Polymer Competence Center Leoben GmbH, Leoben, Austria. · Chair of Materials Science and Testing of Polymers, Montanuniversitat Leoben, Leoben, Austria.

  18. Anomaly Detection via Autoencoder Composite Features and NCE

    Feb 4, 2025Yalin Liao, Austin J. BrockmeierUnsupervised Anomaly DetectionReconstruction-Based Anomaly Detection

    Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware · Department of Electrical and Computer Engineering, Department of Computer and Information Sciences, University of Delaware, Newark, Delaware

  19. Tuned Reverse Distillation: Enhancing Multimodal Industrial Anomaly Detection with Crossmodal Tuners

    Dec 12, 2024Xinyue Liu, Jianyuan Wang, Biao Leng +1Cross-Modal Knowledge DistillationIndustrial Anomaly Detection

    School of Computer Science and Engineering, Beihang University, Beijing 100191, China · Key Laboratory of Intelligent Bionic Unmanned Systems, Ministry of Education, and the School of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China · School of Computer Science and Technology, Beijing Jiaotong University, Beijing 100044, China