你好! Shipping to Taiwan with premium packaging for just NT$300 

Ship to
Taiwan
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics (Springerbriefs in Complexity)
Type
Physical Book
Publisher
Author
Language
English
Pages
128
Format
Paperback
ISBN13
9783319694368
Edition No.
1

Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics (Springerbriefs in Complexity)

Tiziano Squartini; Diego Garlaschelli (Author) · Springer · Paperback

Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics (Springerbriefs in Complexity) - Tiziano Squartini; Diego Garlaschelli

Cheaper New Book Imported to Taiwan
Delivery: 23 Sep - 06 Oct Shipping: 13 to 17 business days.
NT$ 2,303
Faster New Book Imported to Taiwan
Delivery: 11 Sep - 21 Sep Shipping: 5 to 6 business days.
NT$ 2,653
NT$ 2,303

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Maximum-Entropy Networks: Pattern Detection, Network Reconstruction and Graph Combinatorics (Springerbriefs in Complexity)"

This book is an introduction to maximum-entropy models of random graphs with given topological properties and their applications. Its original contribution is the reformulation of many seemingly different problems in the study of both real networks and graph theory within the unified framework of maximum entropy. Particular emphasis is put on the detection of structural patterns in real networks, on the reconstruction of the properties of networks from partial information, and on the enumeration and sampling of graphs with given properties. After a first introductory chapter explaining the motivation, focus, aim and message of the book, chapter 2 introduces the formal construction of maximum-entropy ensembles of graphs with local topological constraints. Chapter 3 focuses on the problem of pattern detection in real networks and provides a powerful way to disentangle nontrivial higher-order structural features from those that can be traced back to simpler local constraints. Chapter 4 focuses on the problem of network reconstruction and introduces various advanced techniques to reliably infer the topology of a network from partial local information. Chapter 5 is devoted to the reformulation of certain "hard" combinatorial operations, such as the enumeration and unbiased sampling of graphs with given constraints, within a "softened" maximum-entropy framework. A final chapter offers various overarching remarks and take-home messages.By requiring no prior knowledge of network theory, the book targets a broad audience ranging from PhD students approaching these topics for the first time to senior researchers interested in the application of advanced network techniques to their field.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews