๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Probabilistic Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning)

โœ Scribed by Daphne Koller, Nir Friedman


Publisher
The MIT Press
Year
2009
Tongue
English
Leaves
1266
Edition
1
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Probabilistic Graphical Models: Principl
โœ Daphne Koller, Nir Friedman ๐Ÿ“‚ Library ๐Ÿ“… 2009 ๐Ÿ› The MIT Press ๐ŸŒ English

Most tasks require a person or an automated system to reason--to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be cons

Probabilistic graphical models : princip
โœ Daphne Koller; Nir Friedman ๐Ÿ“‚ Library ๐Ÿ“… 2009 ๐Ÿ› MIT Press ๐ŸŒ English

1. Introduction -- 2. Foundations -- I. Representation -- 3. Bayesian Network Representation -- 4. Undirected Graphical Models -- 5. Local Probabilistic Models -- 6. Template-Based Representations -- 7. Gaussian Network Models -- 8. Exponential Family -- II. Inference -- 9. Exact Inference: Variabl

Probabilistic Graphical Models: Principl
โœ Daphne Koller, Nir Friedman ๐Ÿ“‚ Library ๐Ÿ“… 2009 ๐Ÿ› The MIT Press ๐ŸŒ English

<p><b>A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.</b></p><p>Most tasks require a person or an automated system to reason -- to reach conclusions based on available information.