{"data":{"slug":"yzhao062-anomaly-detection-resources","name":"anomaly-detection-resources","tagline":"Anomaly detection related 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":9364,"forks":1805,"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":16,"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":281,"ai_summary":"A collection of resources for anomaly detection including books, papers, online courses, datasets, and libraries/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":"2026-08-17T06:02:04.648302+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"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"anomaly-detection","name":"anomaly-detection"},{"slug":"awesome-list","name":"awesome-list"},{"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"},{"slug":"time-series-analysis","name":"time-series-analysis"}],"trust":{"provenance":{"is_fork":false,"github_id":133717148,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-17T06:02:03.583Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":168,"last_release_at":null,"stars_delta_30d":16,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:02:36.870Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-17T06:02:04.317Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-17T06:02:04.317Z"},"license_spdx":{"value":"AGPL-3.0","source":"github.license","observed_at":"2026-08-17T06:02:04.317Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need extensive learning resources on outlier detection techniques","Interested in the latest Large Language Model (LLM) and Vision-Language Model (VLM) works for anomaly detection"],"when_not_to_use":["Require proprietary or commercial tools with restrictive licenses","Looking for a standalone tool rather than a collection of resources"],"source":"enrich:decision_facts","observed_at":"2026-07-12T17:05:22.242Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"anomaly-detection-resources: Comprehensive collection of anomaly detection materials including books, courses, datasets, libraries with an AGPL-3.0 license."}]}}