{"data":{"slug":"yzhao062-anomaly-detection-resources","name":"anomaly-detection-resources","tagline":"Anomaly detection resources including books, papers, videos, and toolboxes","github_url":"https://github.com/yzhao062/anomaly-detection-resources","owner":"yzhao062","repo":"anomaly-detection-resources","owner_avatar_url":"https://avatars.githubusercontent.com/u/15079146?v=4","primary_language":"Python","stars":9388,"forks":1801,"topics":["anomaly-detection","awesome","awesome-list","data-mining","fraud","fraud-detection","graph-neural-networks","large-language-models","llm","machine-learning","outlier","outlier-detection","outlier-ensembles","time-series-analysis","unsupervised-learning","vlm","vlms"],"archived":false,"github_pushed_at":"2026-03-02T04:42:20+00:00","maintenance_label":"Slowing","stars_delta_30d":24,"url":"https://www.graphcanon.com/tools/yzhao062-anomaly-detection-resources","markdown_url":"https://www.graphcanon.com/tools/yzhao062-anomaly-detection-resources.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/yzhao062-anomaly-detection-resources","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=yzhao062-anomaly-detection-resources","description":"Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!","homepage_url":null,"license":"AGPL-3.0","open_issues":14,"watchers":286,"ai_summary":"A collection of anomaly detection learning resources such as books, academic papers, online courses, videos, datasets, and toolkits","readme_excerpt":"Anomaly Detection Learning Resources\n====================================\n\n.. image:: https://img.shields.io/github/stars/yzhao062/anomaly-detection-resources.svg\n   :target: https://github.com/yzhao062/anomaly-detection-resources/stargazers\n   :alt: GitHub stars\n\n\n.. image:: https://img.shields.io/github/forks/yzhao062/anomaly-detection-resources.svg?color=blue\n   :target: https://github.com/yzhao062/anomaly-detection-resources/network\n   :alt: GitHub forks\n\n\n.. image:: https://img.shields.io/github/license/yzhao062/anomaly-detection-resources.svg?color=blue\n   :target: https://github.com/yzhao062/anomaly-detection-resources/blob/master/LICENSE\n   :alt: License\n\n\n.. image:: https://awesome.re/badge-flat2.svg\n   :target: https://awesome.re/badge-flat2.svg\n   :alt: Awesome\n\n\n.. image:: https://img.shields.io/badge/ADBench-benchmark_results-pink\n   :target: https://github.com/Minqi824/ADBench\n   :alt: Benchmark\n\n\n----\n\n`Outlier Detection <https://en.wikipedia.org/wiki/Anomaly_detection>`_\n(also known as *Anomaly Detection*) is an exciting yet challenging field,\nwhich aims to identify outlying objects that are deviant from the general data distribution.\nOutlier detection has been proven critical in many fields, such as credit card\nfraud analytics, network intrusion detection, and mechanical unit defect detection.\n\n**This repository collects**:\n\n\n#. Books & Academic Papers \n#. Online Courses and Videos\n#. Outlier Datasets\n#. Open-source and Commercial Libraries/Toolkits\n#. Key Conferences & Journals\n\n\n**More items will be added to the repository**.\nPlease feel free to suggest other key resources by opening an issue report,\nsubmitting a pull request, or dropping me an email @ (yzhao010@usc.edu).\nEnjoy reading!\n\nBTW, you may find my `[GitHub] <https://github.com/yzhao062>`_, `[USC FORTIS Lab] <https://github.com/USC-FORTIS>`_, and\n`[Google Scholar] <https://scholar.google.com/citations?user=zoGDYsoAAAAJ&hl=en>`_ relevant,\nespecially `PyOD library <https://github.com/yzhao062/pyod>`_, `ADBench benchmark <https://github.com/Minqi824/ADBench>`_, and `NLP-ADBench: NLP Anomaly Detection Benchmark  <https://github.com/USC-FORTIS/NLP-ADBench>`_,.\n\n----\n\nTable of Contents\n-----------------\n\n\n* `1. Books & Tutorials & Benchmarks <#1-books--tutorials--benchmarks>`_\n\n  * `1.1. Benchmarks <#13-benchmarks>`_\n  * `1.2. Tutorials <#12-tutorials>`_\n  * `1.3. Books <#11-books>`_\n\n* `2. Courses/Seminars/Videos <#2-coursesseminarsvideos>`_\n* `3. Toolbox & Datasets <#3-toolbox--datasets>`_\n\n  * `3.1. Multivariate data outlier detection <#31-multivariate-data>`_\n  * `3.2. Time series outlier detection <#32-time-series-outlier-detection>`_\n  * `3.3. Graph Outlier Detection <#33-graph-outlier-detection>`_\n  * `3.4. Real-time Elasticsearch <#34-real-time-elasticsearch>`_\n  * `3.5. Datasets <#35-datasets>`_\n\n* `4. Papers <#4-papers>`_\n\n  * `4.1. LLM and LLM Agents for Anomaly Detection <#41-llm-and-llm-agents-for-anomaly-detection>`_\n  * `4.2. Emerging and Interesting Topics <#42-emerging-and-interesting-topics>`_\n  * `4.3. Weakly-supervised Methods <#43-weakly-supervised-methods>`_\n  * `4.4. Machine Learning Systems for Outlier Detection <#44-machine-learning-systems-for-outlier-detection>`_\n  * `4.5. Automated Outlier Detection <#45-automated-outlier-detection>`_\n  * `4.6. Outlier Detection with Neural Networks <#46-outlier-detection-with-neural-networks>`_\n  * `4.7. Interpretability <#47-interpretability>`_\n  * `4.8. Representation Learning in Outlier Detection <#48-representation-learning-in-outlier-detection>`_\n  * `4.9. Outlier Detection in Evolving Data <#49-outlier-detection-in-evolving-data>`_\n  * `4.10. Outlier Ensembles <#410-outlier-ensembles>`_\n  * `4.11. High-dimensional & Subspace Outliers <#411-high-dimensional--subspace-outliers>`_\n  * `4.12. Feature Selection in Outlier Detection <#412-feature-selection-in-outlier-detection>`_\n  * `4.13. Time Series Outlier Detection <#413-time-series-outlier-detection>`_\n  * `4.14. Graph & Network Outlier","github_created_at":"2018-05-16T20:02:54+00:00","created_at":"2026-07-07T17:34:09.91335+00:00","updated_at":"2026-09-20T04:33:47.081724+00:00","categories":[{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"anomaly-detection","name":"anomaly-detection"},{"slug":"awesome-list","name":"awesome-list"},{"slug":"data-mining","name":"data-mining"},{"slug":"fraud-detection","name":"fraud-detection"},{"slug":"graph-neural-networks","name":"graph-neural-networks"},{"slug":"large-language-models","name":"large-language-models"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"outlier-detection","name":"outlier-detection"}],"trust":{"provenance":{"is_fork":false,"github_id":133717148,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:50:28.981Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":200,"last_release_at":null,"stars_delta_30d":24,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:50:30.603Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:50:27.889Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-09-18T08:50:27.889Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-09-18T08:50:27.889Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":[],"min_ram_gb":null,"requires_docker":false},"constraints":{"min_ram_gb":null,"requires_docker":false},"when_to_use":["when you need a curated list of resources for learning about anomaly detection, including books, academic papers, and toolkits.","if you are looking for datasets specifically for anomaly detection, as the repository includes a section dedicated to outlier datasets.","when you are interested in the latest developments in large language models (LLM) and vision language models (VLM) for anomaly detection, as the repository is updated to include these advancements."],"when_not_to_use":["if you require real-time anomaly detection services, as the repository focuses on educational resources and toolkits rather than live monitoring tools.","when you need a specific tool for real-time anomaly detection in Elasticsearch, as the repository provides resources but not a dedicated real-time service.","if you are looking for a single, integrated tool for anomaly detection rather than a collection of resources, as this repository is a compilation of various materials and not a standalone tool."],"source":"enrich:decision_facts","observed_at":"2026-09-18T12:03:51.501Z"},"constraint_facets":{"min_ram_gb":null,"requires_docker":false},"decision_summary":[{"label":"Adopt for","value":"Anomaly-detection-resources is a comprehensive collection of learning materials and tools for anomaly detection, including books, papers, videos, and toolkits. 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