概率图模型

Hacker News 上怎么说

• boltzmannbrain · 2018 年

  ……做了大约 6 年的 AI 研究工程师。[1] https://www.amazon.com/Artificial-Intelligence-Modern-Approa... [2] https://www.amazon.com/Pattern-Recognition-Learning-Informat... [3] https://www.amazon.com/Probabilistic-Graphical-Models-Princi... [4] https://youtu.be/-z5lKPHcumo

  …AI research engineer for ~6 years. [1] https://www.amazon.com/Artificial-Intelligence-Modern-Approa... [2] https://www.amazon.com/Pattern-Recognition-Learning-Informat... [3] https://www.amazon.com/Probabilistic-Graphical-Models-Princi... [4] https://youtu.be/-z5lKPHcumo

• maurits · 2014 年

  ……van der Heijden 写的《参数估计与状态估计》（Parameter Estimation and State Estimation）。http://prtools.org Prince 写的《计算机视觉：模型、学习与推理》（Computer Vision: Models, Learning, and Inference），免费提供 http://www.computervisionmodels.com/ Koller 写的《概率图模型》（Probabilistic Graphical Models）。在 Coursera 上有配套课程。

  …Parameter Estimation and State Estimation, by van der Heijden. http://prtools.org Computer Vision: Models, Learning, and Inference, by Prince, available for free http://www.computervisionmodels.com/ Probabilistic Graphical Models, by Koller. Has an accompanying course on Coursera.

• shogunmike · 2015 年

  ……分析（Gellman）：http://www.amazon.com/Bayesian-Analysis-Chapman-Statistical-... 贝叶斯推理与机器学习（Barber）：http://www.amazon.com/Bayesian-Reasoning-Machine-Learning-Ba... 概率图模型（Koller 等）：https://www.coursera.org/course/pgm http://www.amazon.com/Probabilistic-Graphical-Models-Princip... 如果你想从更偏数学/统计的角度来学习机器学习，那么这两本……

  …Analysis (Gellman): http://www.amazon.com/Bayesian-Analysis-Chapman-Statistical-... Bayesian Reasoning and Machine Learning (Barber): http://www.amazon.com/Bayesian-Reasoning-Machine-Learning-Ba... Probabilistic Graphical Models (Koller et al): https://www.coursera.org/course/pgm http://www.amazon.com/Probabilistic-Graphical-Models-Princip... If you want a more mathematical/statistical take on Machine Learning, then the two…

• adamnemecek · 2016 年

  ……学习（http://www.deeplearningbook.org/ 或 https://smile.amazon.com/Deep-Learning-Adaptive-Computation-...）* 神经网络与深度学习（http://neuralnetworksanddeeplearning.com/）进阶：* 概率图模型：原理与技术（https://smile.amazon.com/Probabilistic-Graphical-Models-Prin...）我还发现了解一下概率编程也很有帮助。这几个资源都相当不错：……

  …Learning (http://www.deeplearningbook.org/ or https://smile.amazon.com/Deep-Learning-Adaptive-Computation-...) * Neural Networks and Deep Learning (http://neuralnetworksanddeeplearning.com/) Advanced: * Probabilistic Graphical Models: Principles and Techniques (https://smile.amazon.com/Probabilistic-Graphical-Models-Prin...) I have also found that looking into probabilistic programming is helpful too. These resources are pretty good:…

• aaronharnly · 2013 年

  虽然它讲的远不止 MCMC，但 Daphne Koller（Coursera 创始人之一）和 Nir Friedman 合著的《概率图模型》教材是对该领域的详尽介绍。书中对 MCMC 的探讨能让你获得比那种泛泛而谈浅尝辄止的内容深刻得多的理解……

  It has much more than MCMC, but the "Probabilistic Graphical Models" textbook by Daphne Koller (of Coursera) and Nir Friedman is a thorough introduction to the subject. It includes a discussion of MCMC that will leave you with a deeper understanding than the typical shallow…

• jsyedidia · 2010 年

  ……本质上是用同一种“图模型”可视化语言来表达的类似算法。想了解更多内容，可以看 Mezard 和 Montanari 写的《信息、物理与计算》（Information, Physics, and Computation），Koller 和 Friedman 写的《概率图模型》，或者我自己的文章 ;-)。

  …essentially similar algorithms using the same visual language of "graphical models." To learn more about that, see the book on "Information, Physics, and Computation," by Mezard and Montanari, the book on "Probabilistic Graphical Models," by Koller and Friedman, or my own articles ;-).

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