THEORY2

User Tools

Site Tools

Trace:
ml4gamma:biblio

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision		Previous revision
ml4gamma:biblio [21/07/2025 13:55] – [Гамма астрономия] adminml4gamma:biblio [20/01/2026 08:51] (current) – [Редкие, аномальные события] admin
Line 10: Line 10:
   * [[https://logic.pdmi.ras.ru/~sergey/teaching/maderl20/|Лекции по МО Сергея Николенко]]   * [[https://logic.pdmi.ras.ru/~sergey/teaching/maderl20/|Лекции по МО Сергея Николенко]]
   * [[https://habr.com/ru/articles/821547/|Метрики]] в МО   * [[https://habr.com/ru/articles/821547/|Метрики]] в МО
 +  * [[https://habr.com/ru/companies/mws/articles/770202/|Трансформеры]] простыми словами
 +
 +===== Обратимые НС =====
 +
 +  * {{ :ml4gamma:817_analyzing_inverse_problems_wit-1-iclr-2019.pdf |Analyzing Inverse Problems with
 +Invertible Neural Networks}}
 +  * {{ :ml4gamma:inn_final.pdf |Invertible Neural Networks and their Applications}}
 +  * {{ :ml4gamma:inns-cern-october-2020.pdf |Solving Inverse Problems with Invertible Neural Networks}}
 ===== Редкие, аномальные события ===== ===== Редкие, аномальные события =====
  
-**Общие обзоры**+==== Общие обзоры ====
  
   * Liu, Jiaqi, Guoyang Xie, Jinbao Wang, Shangnian Li, Chengjie Wang, Feng Zheng, and Yaochu Jin. [[https://link.springer.com/article/10.1007/s11633-023-1459-z|"Deep industrial image anomaly detection: A survey."]] Machine Intelligence Research 21, no. 1 (2024): 104-135.    * Liu, Jiaqi, Guoyang Xie, Jinbao Wang, Shangnian Li, Chengjie Wang, Feng Zheng, and Yaochu Jin. [[https://link.springer.com/article/10.1007/s11633-023-1459-z|"Deep industrial image anomaly detection: A survey."]] Machine Intelligence Research 21, no. 1 (2024): 104-135. 
Line 22: Line 30:
     * Обзор только литературных источников по базовым критериям (type, ML model, performance metrics and their value, etc.), но очень объемлющий (более 300 ссылок)      * Обзор только литературных источников по базовым критериям (type, ML model, performance metrics and their value, etc.), но очень объемлющий (более 300 ссылок) 
  
- **GAN для поиска аномалий**+==== GAN для поиска аномалий ====
  
   * Di Mattia, Federico, Paolo Galeone, Michele De Simoni, and Emanuele Ghelfi. [[https://arxiv.org/pdf/1906.11632|"A survey on gans for anomaly detection."]] arXiv preprint arXiv:1906.11632 (2019).    * Di Mattia, Federico, Paolo Galeone, Michele De Simoni, and Emanuele Ghelfi. [[https://arxiv.org/pdf/1906.11632|"A survey on gans for anomaly detection."]] arXiv preprint arXiv:1906.11632 (2019). 
Line 34: Line 42:
       * [[https://www.toolify.ai/ai-news/advanced-anomaly-detection-with-bigans-for-image-data-1284376|Advanced Anomaly Detection with BiGANs for Image Data]]        * [[https://www.toolify.ai/ai-news/advanced-anomaly-detection-with-bigans-for-image-data-1284376|Advanced Anomaly Detection with BiGANs for Image Data]] 
  
-**Поиск аномальных данных IACT**+==== Поиск аномальных данных IACT ====
  
   * De, Songshaptak, Writasree Maitra, Vikram Rentala, and Arun M. Thalapillil. [[https://arxiv.org/pdf/2206.05296|"Deep learning techniques for imaging air Cherenkov telescopes."]] Physical Review D 107, no. 8 (2023): 083026.   * De, Songshaptak, Writasree Maitra, Vikram Rentala, and Arun M. Thalapillil. [[https://arxiv.org/pdf/2206.05296|"Deep learning techniques for imaging air Cherenkov telescopes."]] Physical Review D 107, no. 8 (2023): 083026.
Line 52: Line 60:
 ===== Гамма астрономия ===== ===== Гамма астрономия =====
  
-Очень красивая презентация [[https://gammalearn.pages.in2p3.fr/talks/20250128-ml-cosmic-workshop/|GammaLearn - Deep Learning for the CTAO event reconstruction]] +  * Очень красивая презентация [[https://gammalearn.pages.in2p3.fr/talks/20250128-ml-cosmic-workshop/|GammaLearn - Deep Learning for the CTAO event reconstruction]] 
 +  * D. Bose, V. R. Chitnis, P. Majumdar, and B. S.Acharya. {{ :ml4gamma:s11734-021-00396-3-ground_based_gra.pdf |Ground-based gamma-ray astronomy: history and development of techniques}}
   * Ti-Pei Li and  YuQian Ma, Analysis methods for results in gamma-ray astronomy, [[https://www.researchgate.net/publication/234438870|ResearchGate]], in The Astrophysical Journal, August 1983   * Ti-Pei Li and  YuQian Ma, Analysis methods for results in gamma-ray astronomy, [[https://www.researchgate.net/publication/234438870|ResearchGate]], in The Astrophysical Journal, August 1983
   * Tilman Plehna, Anja Buttera, Barry Dillona, and Claudius Krausea. Modern Machine Learning for LHC Physicists. [[https://arxiv.org/pdf/2211.01421v1|ArXiv: 2211.01421v1]]   * Tilman Plehna, Anja Buttera, Barry Dillona, and Claudius Krausea. Modern Machine Learning for LHC Physicists. [[https://arxiv.org/pdf/2211.01421v1|ArXiv: 2211.01421v1]]
ml4gamma/biblio.1753106158.txt.gz · Last modified: by admin