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. Rethinking Structural Anomaly Detection: From Decision Boundaries to Projection Operators

    Jun 13, 2026Alexander BauerReconstruction-Based Anomaly DetectionAnomaly Detection

    Machine Learning Group, TU Berlin · BIFOLD, Berlin, Germany

  2. BoRAD: Bootstrap your Own Representations for Multi-class Anomaly Detection

    Jun 12, 2026Duy Hoang Khuong, Tri Nguyen Minh, Ngu Huynh Cong VietRepresentation LearningIndustrial Anomaly Detection

    Department of Artificial Intelligence FPT University Ho Chi Minh City, Vietnam · Department of IT FPT University Ho Chi Minh City, Vietnam · Department of Computing Fundamental FPT University Ho Chi Minh City, Vietnam

  3. A Zero-shot Generalized Graph Anomaly Detection Framework via Node Reconstruction

    Jun 10, 2026Phan Nguyen, Dat Cao, Hien Chu +1Cross-Domain GeneralizationReconstruction-Based Anomaly Detection

    School of Computing, KAIST

  4. Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices

    Jun 10, 2026Kaan Arda Akyol, Jakub Kacper Szeląg, Aydin Abadi +9Electrocardiogram ClassificationReconstruction-Based Anomaly Detection

    School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom

  5. Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision

    Jun 8, 2026Mateo Diaz-Bone, Daniel Caraballo, Florian Scheidegger +11Anomaly LocalizationReconstruction-Based Anomaly Detection

    IBM Research Europe Zurich, Switzerland

  6. AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection

    Jun 7, 2026Md Mahfuzur Rahman Siddiquee, Fazle Rafsani, Jay Shah +4Medical Image Anomaly DetectionReconstruction-Based Anomaly Detection

    School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281 · Mayo Clinic, Arizona

  7. Anomaly Detection for Electro-Hydrostatic Actuators using LSTM Autoencoder

    Jun 3, 2026Nehal Afifi, Abdelmonem Elhendawi, Felix Leitenberger +2Industrial Anomaly DetectionReconstruction-Based Anomaly Detection

    IPEK - Institute of Product Engineering, Karlsruhe Institute of Technology (KIT), Germany. · SUPMICROTECH-ENSMM, France.

  8. ReConFuse: Reconstruction-Error Guided Semantic Fusion for AI-Generated Video Detection

    Jun 3, 2026Xiaojing Chen, Xinyu Lu, Changtao Miao +1Deepfake DetectionReconstruction-Based Anomaly Detection

    Anhui University · Ant Group · Hefei University of Technology

  9. Disjoint or Overlapping? Inference Windowing for Reconstruction-Based Time Series Anomaly Detection

    Jun 2, 2026Guillaume Coulaud, Reza Akbarinia, Florent MassegliaReconstruction-Based Anomaly DetectionTime-Series Anomaly Detection

    UM, IROKO · University of Montpellier, Inria, CNRS, LIRMM, Montpellier, France · IROKO +1

  10. Trans GAN-WT: A Feature Extraction and Interactive Learning-Based Anomaly Detection Model for Wind Turbine Time Series Data

    Jun 2, 2026Jingzhe KangReconstruction-Based Anomaly DetectionTime-Series Anomaly Detection

    School of Mathematics, Shandong University, Jinan 250100, China

  11. ArrythML: An Autoencoder-Based TinyML Approach for On-Device Arrhythmia Detection on Resource-Constrained Embedded Systems

    Jun 1, 2026Nagarajan S, Kurian PolachanElectrocardiogram ClassificationReconstruction-Based Anomaly Detection

    International Institute of Information Technology, Bangalore, India

  12. IstGPT: LLM-based Anomaly Detection for Spatial-Temporal Graph in Industrial Systems

    Jun 1, 2026Yuchen Zhang, Ning Xi, Pengbin Feng +5Cyber-Physical SystemsIndustrial Anomaly Detection

    School of Cyber Engineering, Xidian University, Xi’an 710126, China · School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC, Australia · School of Computer Science and Technology, Xidian University, Xi’an 710126, China

  13. Deep-learning-based low-energy trigger algorithms for the Hyper-Kamiokande experiment

    May 29, 2026Katharina Lachner, Saúl Alonso-Monsalve, Benjamin Richards +1High-Energy PhysicsReconstruction-Based Anomaly Detection

    ETH Zürich · University of Warwick

  14. Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection

    May 25, 2026Qideng Tang, Dai Chaofan, Wubin Ma +5Reconstruction-Based Anomaly DetectionTime-Series Anomaly Detection

    National Key Laboratory of Information Systems Engineering, National University of Defense Technology Changsha, Hunan, China · Also with Zhejiang Key Laboratory of Space Information Sensing and Transmission, Hangzhou Dianzi University. · College of Systems Engineering, National University of Defense Technology Changsha, Hunan, China +2

  15. Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces

    May 23, 2026Yaoxuan Feng, Yuxin Li, Weijiang Lv +5Prototype LearningIndustrial Anomaly Detection

    National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an, 710071, China.

  16. Self-Supervised ConvLSTM for Fermi Large Area Telescope Transient Detection

    May 21, 2026Alberto Garinei, Stefano Speziali, Alessandro Vispa +11Convolutional LSTMHigh-Energy Physics

    Idea-Re S.r.l., 06125, Perugia, Italy · bDipartimento Scienze Ingegneristiche, Università Guglielmo Marconi, 00193, Rome, Italy · cIstituto Nazionale Fisica Nucleare, sezione di Perugia, 06123, Perugia, Italy +1

  17. TERGAD: Structure-Aware Text-Enhanced Representations for Graph Anomaly Detection

    May 19, 2026Wen Shi, Zhe Wang, Huafei Huang +6Graph Representation LearningText-Attributed Graph Learning

    College of Computer Science and Technology, Jilin University, Changchun 130012, China · School of Computer Science and Information Technology, Adelaide University, Adelaide SA5095, Australia · School of Computing Technologies, RMIT University, Melbourne, VIC 3000, Australia +1

  18. Learning Unified Representations of Normalcy for Time Series Anomaly Detection

    May 10, 2026Prithul Sarker, Sushmita Sarker, Nicholas G. Murray +1Reconstruction-Based Anomaly DetectionUnsupervised Anomaly Detection

    University of Nevada, Reno

  19. FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection

    May 10, 2026Yunfeng Zhao, Yixin Liu, Qingfeng Chen +3Federated Graph LearningReconstruction-Based Anomaly Detection

    Guangxi University · Griffith University

  20. GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training

    May 8, 2026Henghui Xu, Yuchen Zhang, Xiaobo MaNetwork Intrusion DetectionReconstruction-Based Anomaly Detection

    MOE Key Laboratory for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, China · Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China · Shaanxi Province Key Laboratory of Computer Network, Xi’an Jiaotong2026 University, Xi’an, China

  21. Two Steps Are All You Need: Efficient 3D Point Cloud Anomaly Detection with Consistency Models

    May 6, 2026Pranav A, Shashank B, Pranav Siddappa +3Point Cloud Anomaly DetectionIndustrial Anomaly Detection

    1R.V. College of Engineering · 2Technical University of Applied Sciences Würzburg-Schweinfurt

  22. Decompose to Understand, Fuse to Detect: Frequency-Decoupled Anomaly Detection for Encrypted Network Traffic

    May 3, 2026Xinglin Lian, Chengtai Cao, Ting Zhong +3Frequency-Domain Feature LearningNetwork Intrusion Detection

    School of Information and Software Engineering, University of Electronic Science and Technology of China · Department of Computer Science, City University of Hong Kong · Department of Computer Science and Engineering, Hong Kong University of Science and Technology +1

  23. Scalable Context-Aware Graph Attention for Unsupervised Anomaly Detection in Large-Scale Mobile Networks

    May 1, 2026Sara Malacarne, Eirik Hoel-Høiseth, Erlend Aune +2Graph Attention NetworksReconstruction-Based Anomaly Detection

    Telenor Research and Innovation, Norway · Norwegian University of Science and Technology (NTNU), Norway · Hance, Norway +2

  24. PhaseNet++: Phase-Aware Frequency-Domain Anomaly Detection for Industrial Control Systems via Phase Coherence Graphs

    Apr 30, 2026Raviteja Bommireddy, Varshith Bandaru, Lohith Pakala +1Cyber-Physical SystemsFrequency-Domain Feature Learning

    Department of CSE IIITDM Kancheepuram Chennai, India

  25. Context-Aware Graph Attention for Unsupervised Telco Anomaly Detection

    Apr 29, 2026Sara Malacarne, Eirik Hoel-Høiseth, Erlend Aune +2Graph Attention NetworksReconstruction-Based Anomaly Detection

    Telenor Research and Innovation, Norway · Norwegian University of Science and Technology (NTNU), Norway · Hance, Norway +2

  26. Unsupervised Graph Modeling for Anomaly Detection in Accounting Subject Relationships

    Apr 29, 2026Yuhan Wang, Ruobing Yan, Zhe Su +3Anomaly LocalizationReconstruction-Based Anomaly Detection

    Columbia University, New York, USA · Georgetown University, Washington, D.C., USA · Pepperdine University, Malibu, USA +2

  27. Anatomy-Aware Unsupervised Detection and Localization of Retinal Abnormalities in Optical Coherence Tomography

    Apr 24, 2026Tania Haghighi, Sina Gholami, Hamed Tabkhi +1Medical ImagingMedical Image Anomaly Detection

    University of North Carolina at Charlotte Charlotte, NC, USA

  28. Back to Repair: A Minimal Denoising Network for Time Series Anomaly Detection

    Apr 19, 2026Kadir-Kaan Özer, René Ebeling, Markus EnzweilerReconstruction-Based Anomaly DetectionTime-Series Anomaly Detection

    Mercedes-Benz AG, Germany · Institute for Intelligent Systems, Esslingen University of Applied Sciences, Germany

  29. NK-GAD: Neighbor Knowledge-Enhanced Unsupervised Graph Anomaly Detection

    Apr 17, 2026Zehao Wang, Lanjun WangGraph Neural NetworksReconstruction-Based Anomaly Detection

    College of Intelligence and Computing, Tianjin University, Tianjin, China · School of New Media and Communication, Tianjin University, Tianjin, China

  30. Unsupervised Anomaly Detection in Process-Complex Industrial Time Series: A Real-World Case Study

    Apr 15, 2026Sergej Krasnikov, Lukas Meitz, Samineh Bagheri +3Time-Series Anomaly DetectionIndustrial Anomaly Detection

    Universität Augsburg Augsburg, Germany · Technische Hochschule Augsburg Augsburg, Germany · Independent Researcher Karlsruhe, Germany