Reconstruction-Based Anomaly Detection

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22 papers in the last four weeks, up 267% on the four weeks before. 0.1% of all new papers.

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  1. Benchmarking Deep Learning Models for Anomaly Detection in Real-World Cloud Telemetry

    Oct 11, 2026Sumit Dhyani, Sougata MukherjeaTime-Series Anomaly DetectionAnomaly Detection

    Electrical Engineering Department, Indian Institute of Technology, Delhi, India

  2. Correlation-Aware Reconstruction for Multivariate Time Series Anomaly Detection

    Oct 11, 2026Md. Johir Raihan, Zahra Zamanzadeh Darban, Yueyang Liu +3Time-Series Anomaly DetectionAnomaly Detection

    Monash University, Melbourne, Victoria, Australia · University of New South Wales, Sydney, New South Wales, Australia

  3. Local Diagnostics of Learned Event Representations for Anomaly Detection at the HL-LHC

    Oct 9, 2026Donatella Genovese, Philip Ploner, Simone Scardapane +2Anomaly DetectionInterpretable Anomaly Detection

    Department of Computer, Control and Management Engineering, Sapienza University of Rome · Department of Physics, ETH Zurich · Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome +1

  4. NV-Tesseract-AD: Curriculum-Enhanced Conditional Diffusion for Multivariate Time-Series Anomaly Detection

    Oct 8, 2026Aditi Gautam, Manikandan Ravikiran, Saira Qureshi +4Time-Series Anomaly DetectionReconstruction-Based Anomaly Detection

    NVIDIA

  5. Unsupervised Maneuver-Aware Acoustic Fault Detection for Autonomous Drones

    Oct 7, 2026Ali M Ali, Ziyi Tang, Nurdaulet Nazarbay +1Fault DetectionUnsupervised Anomaly Detection

    Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON, K1S-5B6, Canada · Department of Electrical and Computer Engineering at the University of Alberta, Edmonton, AB, Canada · The Hong Kong Polytechnic University, Hong Kong

  6. Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection

    Oct 7, 2026Limon Bin Hossain, Md Sadib Rahman AnantaAnomaly DetectionIndustrial Anomaly Detection

    Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, 1000, Bangladesh

  7. A Multi-Source Ultrasound Benchmark Revealing the Limits of Contemporary Self-Supervised Anomaly Detection Methods

    Oct 7, 2026Marco Riedenauer, Daniel Kienzle, Pratik Mayekar +1Medical Image Anomaly DetectionUnsupervised Anomaly Detection

    University of Augsburg

  8. Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection

    Oct 7, 2026Shouhei Hanaoka, Takahiro Nakao, Atsushi Takamatsu +2Medical Image Anomaly DetectionUnsupervised Anomaly Detection

    Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan · Department of Computational Diagnostic Radiology and Preventive Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan · Department of Radiology, Kanazawa University Hospital, 13-1 Takara-machi, Kanazawa, Ishikawa, 920-8641, Japan

  9. MORA: Modeling Observed Changes for Drift-Robust Time-Series Anomaly Detection

    Oct 7, 2026Xudong Mou, Tiejun Wang, Rui Wang +5Time-Series Anomaly DetectionNon-Stationary Time Series

    Beihang University, Beijing, China · Beihang Hangzhou Innovation Institute, Hangzhou, China · China University of Geosciences (Beijing), Beijing, China

  10. GRC-Net: Global Representation Consistency Network for Unsupervised Multimodal Anomaly Detection

    Oct 7, 2026Seyoung Jeong, Jong Pil Yun, Sang Jun LeeAnomaly DetectionIndustrial Anomaly Detection

    Jeonbuk National University, Jeonju, Republic of Korea · Korea Institute of Industrial Technology (KITECH), Incheon, Republic of Korea · Chung-Ang University, Seoul, Republic of Korea

  11. GCTAuto-encoder: A Cross modal Framework for Security Flaw Detection in IoT Networks

    Oct 5, 2026Najmieh Sadat SafarabadiCross-Modal LearningIoT Intrusion Detection

    Department of Computational Linguistics, University of Stuttgart, Stuttgart, Germany.

  12. Normality Constraint Learning: Adapting Foundation Models for Time Series Anomaly Detection

    Oct 5, 2026Xiaohui Zhou, Yijie Wang, Hongzuo Xu +2Reconstruction-Based Anomaly DetectionTime-Series Anomaly Detection

    National Key Laboratory of Parallel and Distributed Computing · College of Computer Science and Technology, National University of Defense Technology · Intelligent Game and Decision Lab (IGDL) +1

  13. Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly Detection

    Sep 30, 2026Ammar Bouketta, Smail Niar, Hamza Ouarnoughi +1Industrial Anomaly DetectionFault Detection

    Universit´e Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, Valenciennes, France · Alstom, Crespin, France · Universit´e Polytechnique Hauts-de-France, LAMIH CNRS UMR 8201, INSA Hauts-de-France, Valenciennes, France +1

  14. LEARN-TS: LLM-Enhanced Alignment and Reconstruction with Normality Guidance for Multivariate Time-Series Anomaly Detection

    Sep 30, 2026Jahyeob Koo, Kio Yun, Byoungmo Koo +1Anomaly LocalizationReconstruction-Based Anomaly Detection

    Department of Industrial and Management Engineering, Korea University Seoul, Republic of Korea

  15. No Scale Left Behind: Multi-Scale Autoencoder with Bi-directional Attention for Time Series Anomaly Detection

    Sep 29, 2026Jiaheng Guo, Haochen Zhang, Yu-Chao Huang +3Reconstruction-Based Anomaly DetectionAttention Mechanisms

    UNITES Lab, University of North Carolina at Chapel Hill

  16. Bayesian Tensor Autoencoder with Physics-informed Predictive Prior for Multi-dimensional Time Series Anomaly Detection

    Sep 25, 2026Jianan Liu, Chunguang LiTime-Series Anomaly DetectionAutoencoders

    Zhejiang University, Hangzhou, China

  17. When Does Unsupervised Learning Succeed or Fail? A PoS Perspective on Reconstruction-Based Anomaly Detection

    Sep 23, 2026Mehmet Yamaç, Yagmur Mustu, Muhammad Numan Yousaf +2Unsupervised Representation LearningReconstruction-Based Anomaly Detection

    Tampere University, Tampere, Finland · Radboud University, Nijmegen, The Netherlands

  18. Beyond Isolated Entities: Relation-Aware Multi-Entity Modeling for Unsupervised Video Anomaly Detection

    Sep 23, 2026Zhongpeng Pan, Xina Cheng, Kailun YangVideo Anomaly DetectionReconstruction-Based Anomaly Detection

    School of Artificial Intelligence, Xidian University, China · School of Artificial Intelligence and Robotics, Hunan University, China · National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, China

  19. Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior

    Sep 21, 2026Hugues Roy, Reuben Dorent, Ninon BurgosMedical Image Anomaly DetectionAnomaly Localization

    Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France

  20. FoundAna: A GNN-assisted Foundation Model for Graph Anomaly Detection

    Sep 16, 2026Suprim Nakarmi, Chahana Dahal, Yue Zhao +2Graph Neural NetworksReconstruction-Based Anomaly Detection

    Department of Computer Science, University of Nevada Las Vegas, Las Vegas, USA · Department of Computer Science, University of Southern California, Los Angeles, USA

  21. Not All Relations Are Equal: Relation-Balanced and Calibrated Graph Learning for Provenance-Based Intrusion Detection

    Sep 15, 2026Lijie Zheng, Ji He, Zhiwei Zhang +3Reconstruction-Based Anomaly DetectionUnsupervised Anomaly Detection

    School of Computer Science and Technology, Xidian University, Xi’an, China

  22. Robust Fault Detection in Mechanical Multimodal Time Series via Self-Supervised Cross-Modal Reconstruction

    Sep 14, 2026Magnus Munk Jensen, Dorte Hammershøi, Rafał Wiśniewski +1Multimodal RobustnessIndustrial Anomaly Detection

    Automation and Control, Aalborg University, Aalborg, Denmark · Intelligent Maintenance and Operations Systems, EPFL, Lausanne, Switzerland

  23. Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar

    Sep 4, 2026Shayan Sharifi, Riccardo Treu, Ilaria Gandin +3Electrocardiogram ClassificationVariational Autoencoders

    Department of Mathematics, Informatics, and Geosciences, University of Trieste, Italy · Centre of Diagnosis and Management of Cardiomyopathies; Azienda Sanitaria Universitaria Giuliano Isontina; University of Trieste, Italy; Member of Ern Guard-Heart · Department of Medical, Surgical and Health Sciences, University of Trieste, Italy

  24. Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data

    Sep 3, 2026Lamine Diop, Marc PlantevitTabular Anomaly DetectionAutoencoders

    EPITA, Laboratoire de Recherche de l’EPITA (LRE) · Le Kremlin-Bicˆetre, France

  25. See More, Detect Less? Taming Information Leakage in Multi-View Anomaly Detection

    Aug 25, 2026Shang-Fu Chen, Kuan-Chuan Peng, Jhih-Ciang Wu +2Anomaly DetectionIndustrial Anomaly Detection

    National Taiwan University Taipei, Taiwan · Mitsubishi Electric Research Laboratories (MERL) Cambridge, MA, USA · National Taiwan Normal University Taipei, Taiwan +2

  26. What Remains Normal? Clean Images Miss Useful Near-Defect Normal Patches for Anomaly Detection

    Aug 24, 2026Joongwon Chae, Runming Wang, Peiwu QinIndustrial Anomaly DetectionReconstruction-Based Anomaly Detection

    Institute of Biopharmaceutical and Health Engineering, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China · RatelSoft · Guangdong Provincial Laboratory of Traditional Chinese Medicine, Hengqin, Guangdong, China

  27. Low-Power, Neuromorphic, Acoustic Anomaly Detection for Persistent Machine Monitoring

    Aug 18, 2026Steven C. Nesbit, Victor M. Vergara, Michael A. Felix +4Anomaly DetectionIndustrial Anomaly Detection

    Information Sciences, CAI-3, Los Alamos National Laboratory, Los Alamos, USA · Information Sciences (CAI-3), Los Alamos National Laboratory, Los Alamos, NM, USA · AeroVironment Inc., Albuquerque, USA +7

  28. Training-Free Reconstruction-Based AI-Generated Image Detectors Are Inherently Vulnerable to Adversarial Examples

    Aug 17, 2026Roman Demchenko, Jonas Ricker, Asja FischerAI-Generated Image DetectionAdversarial Attacks

    Ruhr University Bochum, Bochum, Germany

  29. Revisiting Energy-based Tabular Anomaly Detection: Energy and Reconstruction are Complementary

    Aug 14, 2026Junichiro NiimiTabular Anomaly DetectionEnergy-Based Models

    Meijo University, Nagoya Aichi 4688502, Japan

  30. Contrastive Learning for Interpretable Anomaly Detection at Collider Experiments

    Aug 13, 2026Haoyi Jia, Sagar Addepalli, Julia GonskiAnomaly DetectionInterpretable Anomaly Detection

    Department of Physics, Stanford University, 450 Jane Stanford Way, Stanford, CA 94305 · SLAC National Accelerator Laboratory, 2575 Sand Hill Rd, Menlo Park, CA 94025