Probabilistic Graphical Models : (Record no. 6645)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01455nam a2200181 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20251016145731.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 251008b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783030619459 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 003.54 |
| Item number | SucP |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Sucar, Luis Enrique |
| 245 ## - TITLE STATEMENT | |
| Title | Probabilistic Graphical Models : |
| Remainder of title | Principles and Applications / |
| Statement of responsibility, etc | Luis Enrique Sucar |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Springer : |
| Place of publication | Nature Switzerland , |
| Year of publication | ©2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xxviii,354p. |
| 490 ## - SERIES STATEMENT | |
| Series statement | Advances in Computer Vision and Pattern Recognition |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Purchase Price | Bill number | Full call number | Accession Number | Print Price | Bill Date/Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mathematics | Indian Institute of Technology Tirupati | Indian Institute of Technology Tirupati | General Stacks | 07/10/2025 | Shah Book House | 3570.68 | SBH/28599 | 003.54 SucP (12187) | 12187 | 5100.97 | 07/10/2025 | Books |