Stochastic Epidemic Models with Inference
Stochastic Epidemic Models with Inference

Author: Tom Britton

Publisher: Springer Nature

Published: 2019-11-30

Total Pages: 477

ISBN-13: 3030309002

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Focussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.

Security and Privacy in Social Networks and Big Data
Security and Privacy in Social Networks and Big Data

Author: Limei Lin

Publisher: Springer Nature

Published: 2021-11-16

Total Pages: 194

ISBN-13: 9811679134

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This book constitutes revised and selected papers from the 7th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2021, held in Fuzhou, China, in November 2021. The 16 full papers presented in this volume were carefully reviewed and selected from a total of 41 submissions. Such themes as privacy protection, security of AI, mobile social networks, Big Data system, applied cryptography, and others are covered in the volume.The papers are organized in the following topical sections: ​Applied Cryptography for Big Data; Big Data System Security; Forensics in Social Networks and Big Data; Privacy Protection in Social Networks; Security and Privacy in Big Database; Security of AI; Trust and Reputations in Social Networks.

Hamiltonian Monte Carlo Methods in Machine Learning
Hamiltonian Monte Carlo Methods in Machine Learning

Author: Tshilidzi Marwala

Publisher: Elsevier

Published: 2023-02-03

Total Pages: 222

ISBN-13: 0443190364

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Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical issues of variance reduction for parameter estimates of numerous HMC based samplers. The book offers a comprehensive introduction to Hamiltonian Monte Carlo methods and provides a cutting-edge exposition of the current pathologies of HMC-based methods in both tuning, scaling and sampling complex real-world posteriors. These are mainly in the scaling of inference (e.g., Deep Neural Networks), tuning of performance-sensitive sampling parameters and high sample autocorrelation. Other sections provide numerous solutions to potential pitfalls, presenting advanced HMC methods with applications in renewable energy, finance and image classification for biomedical applications. Readers will get acquainted with both HMC sampling theory and algorithm implementation. - Provides in-depth analysis for conducting optimal tuning of Hamiltonian Monte Carlo (HMC) parameters - Presents readers with an introduction and improvements on Shadow HMC methods as well as non-canonical HMC methods - Demonstrates how to perform variance reduction for numerous HMC-based samplers - Includes source code from applications and algorithms

Mathematical Tools for Understanding Infectious Disease Dynamics
Mathematical Tools for Understanding Infectious Disease Dynamics

Author: Odo Diekmann

Publisher: Princeton University Press

Published: 2013

Total Pages: 516

ISBN-13: 0691155399

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This book explains how to translate biological assumptions into mathematics to construct useful and consistent models, and how to use the biological interpretation and mathematical reasoning to analyze these models. It shows how to relate models to data through statistical inference, and how to gain important insights into infectious disease dynamics by translating mathematical results back to biology.

Stochastic Epidemic Models and Their Statistical Analysis
Stochastic Epidemic Models and Their Statistical Analysis

Author: Hakan Andersson

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 140

ISBN-13: 1461211581

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The present lecture notes describe stochastic epidemic models and methods for their statistical analysis. Our aim is to present ideas for such models, and methods for their analysis; along the way we make practical use of several probabilistic and statistical techniques. This will be done without focusing on any specific disease, and instead rigorously analyzing rather simple models. The reader of these lecture notes could thus have a two-fold purpose in mind: to learn about epidemic models and their statistical analysis, and/or to learn and apply techniques in probability and statistics. The lecture notes require an early graduate level knowledge of probability and They introduce several techniques which might be new to students, but our statistics. intention is to present these keeping the technical level at a minlmum. Techniques that are explained and applied in the lecture notes are, for example: coupling, diffusion approximation, random graphs, likelihood theory for counting processes, martingales, the EM-algorithm and MCMC methods. The aim is to introduce and apply these techniques, thus hopefully motivating their further theoretical treatment. A few sections, mainly in Chapter 5, assume some knowledge of weak convergence; we hope that readers not familiar with this theory can understand the these parts at a heuristic level. The text is divided into two distinct but related parts: modelling and estimation.

Decision and Game Theory for Security
Decision and Game Theory for Security

Author: Fei Fang

Publisher: Springer Nature

Published: 2023-03-12

Total Pages: 324

ISBN-13: 3031263693

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This book constitutes the refereed proceedings of the 13th International Conference on Decision and Game Theory for Security, GameSec 2022, held in October 2022 in Pittsburgh, PA, USA. The 15 full papers presented were carefully reviewed and selected from 39 submissions. The papers are grouped thematically on: deception in security; planning and learning in dynamic environments; security games; adversarial learning and optimization; novel applications and new game models.

Decision and Game Theory for Security
Decision and Game Theory for Security

Author: Quanyan Zhu

Publisher: Springer Nature

Published: 2020-12-21

Total Pages: 518

ISBN-13: 3030647935

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This book constitutes the refereed proceedings of the 11th International Conference on Decision and Game Theory for Security, GameSec 2020,held in College Park, MD, USA, in October 2020. Due to COVID-19 pandemic the conference was held virtually The 21 full papers presented together with 2 short papers were carefully reviewed and selected from 29 submissions. The papers focus on machine learning and security; cyber deception; cyber-physical systems security; security of network systems; theoretic foundations of security games; emerging topics.

Handbook of Infectious Disease Data Analysis
Handbook of Infectious Disease Data Analysis

Author: Leonhard Held

Publisher: CRC Press

Published: 2019-11-07

Total Pages: 567

ISBN-13: 1351839322

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Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material

Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases
Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases

Author: Piero Manfredi

Publisher: Springer Science & Business Media

Published: 2013-01-04

Total Pages: 329

ISBN-13: 1461454743

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This volume summarizes the state-of-the-art in the fast growing research area of modeling the influence of information-driven human behavior on the spread and control of infectious diseases. In particular, it features the two main and inter-related “core” topics: behavioral changes in response to global threats, for example, pandemic influenza, and the pseudo-rational opposition to vaccines. In order to make realistic predictions, modelers need to go beyond classical mathematical epidemiology to take these dynamic effects into account. With contributions from experts in this field, the book fills a void in the literature. It goes beyond classical texts, yet preserves the rationale of many of them by sticking to the underlying biology without compromising on scientific rigor. Epidemiologists, theoretical biologists, biophysicists, applied mathematicians, and PhD students will benefit from this book. However, it is also written for Public Health professionals interested in understanding models, and to advanced undergraduate students, since it only requires a working knowledge of mathematical epidemiology.