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An Introduction to Exponential Random Graph Modeling

Explaining the techniques and applications of exponential random graph modeling (ERGM) for social scientists, this is a uniquely;

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Exponential Random Graph Models for Social Networks

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure;

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Exponential Random Graph Models for Social Networks

Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure;

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Large Deviations for Random Graphs

random graph look like if by chance it has far more triangles than expected? Until recently, probability theory offered no tools to help answer;

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Random Walks and Heat Kernels on Graphs

This introduction to random walks on infinite graphs gives particular emphasis to graphs with polynomial volume growth. It offers an;

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An Introduction to Bond Graph Modeling with Applications

An Introduction to Bond Graph Modeling with Applications presents a collection of exercises on dynamical systems, modeling and control for;

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Inferential Network Analysis

This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation;

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Inferential Network Analysis

This unique textbook provides an introduction to statistical inference with network data. The authors present a self-contained derivation;

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Generating Random Networks and Graphs

theoretical study. This book presents and discusses common methods of generating random graphs. It begins with approaches such as Exponential Random;

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Probability

Improve Your Probability of Mastering This Topic This book takes an innovative approach to calculus-based probability theory, considering;

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A Signal Theoretic Introduction to Random Processes

Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the;

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Characterizations of Exponential Distribution by Ordered Random Variables

. The aim of the book is to present various characterizations of exponential distribution based on ordered random variables. The book is written;

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Statistical and Machine Learning Approaches for Network Analysis

partition biological networks * An introduction to complex networks measures, statistical properties, and models * Modeling for evolving biological;

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Modeling and Simulation of Logistics Flows 1

Volume 1 presents successively an introduction followed by 10 chapters and a conclusion: - A logistic approach - an overview of operations;

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System Dynamics and Control with Bond Graph Modeling

a bond graph perspective. Using an approach that combines bond graph concepts and traditional approaches, the author presents an integrated;

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Graph Searching Games and Probabilistic Methods

, Zombie and Survivors, and Firefighting. Written in an engaging style, the book is accessible to a wide audience including mathematicians and;

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Graph Searching Games and Probabilistic Methods

, Zombie and Survivors, and Firefighting. Written in an engaging style, the book is accessible to a wide audience including mathematicians and;

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Modern Graph Theory

An in-depth account of graph theory, written for serious students of mathematics and computer science. It reflects the current state of the;

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Forecasting with Exponential Smoothing

the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are;

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Graph Theory: An Introduction to Proofs, Algorithms, and Applications

Graph Theory: An Introduction to Proofs, Algorithms, and Applications Graph theory is the study of interactions, conflicts, and;

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Graph Theory: An Introduction to Proofs, Algorithms, and Applications

Graph Theory: An Introduction to Proofs, Algorithms, and Applications Graph theory is the study of interactions, conflicts, and;

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Random Walk

the need for a modern reference to the detailed properties of an important class of random walks on the integer lattice. It is suitable for;

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Introduction to Graph Neural Networks

comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN;

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Introduction to Graph Neural Networks

This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with;

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Random Graph Dynamics

Strogatz and Watts to define the small world random graph in which each site is connected to k close neighbors, but also has long-range connections;

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Graph Representation Learning

applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism;

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Introduction to Mathematical Modeling

Introduction to Mathematical Modeling helps students master the processes used by scientists and engineers to model real-world problems;

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