This book introduces a unified framework that integrates various data-driven information dynamics approaches to quantify node-specific, pairwise, and high-order interactions within complex systems in the contexts of network neuroscience and network physiology.
This book introduces a unified framework that integrates various data-driven information dynamics approaches to quantify node-specific, pairwise, and high-order interactions within complex systems in the contexts of network neuroscience and network physiology.
This volume on visual commonsense reasoning, part of a comprehensive three-volume series, presents a computational framework for bridging the gap between modern computer vision capabilities and human-like visual understanding.
By integrating cutting-edge statistical research with diverse applications, this book serves as both a reference and an inspiration for those interested in advancing Bayesian methodologies.
This monograph focuses on the development of diagnostic procedures for diseases related to retinal nerve conditions using features of waveforms of pupillary light reflex (PLR).
Dieses essential bietet Orientierung, indem es verschiedene Gütekriterien für statistische Indikatoren vorstellt und beispielhaft auf eine Auswahl besonders gesellschaftsrelevanter Indikatoren anwendet – etwa auf Indikatoren zur Messung von Geldwertstabilität, Armut, Klimawandel oder Lebensqualität.
Dieses essential bietet Orientierung, indem es verschiedene Gütekriterien für statistische Indikatoren vorstellt und beispielhaft auf eine Auswahl besonders gesellschaftsrelevanter Indikatoren anwendet – etwa auf Indikatoren zur Messung von Geldwertstabilität, Armut, Klimawandel oder Lebensqualität.
Dentro de la literatura de los metodos kernels, recientemente ha surgido el metodo de embebimiento de distribuciones de probabilidad en espacios de Hilbert con Kernel Reproductivo (RKHS).
Desde las diferentes areas del conocimiento que pretendan ser consideradas como cientificas o cuyas teorias pretendan ser validadas, el uso de la estadistica toma relevancia.
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "e;Augmented Gaussian Process"e; methodology.
This book provides a comprehensive examination of the structure of approximate optimal policies in Markov decision processes (MDPs) with finite state spaces, as well as approximate optimal solutions for deterministic discrete-time optimal control problems.
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, specifically focusing on the novel "e;Augmented Gaussian Process"e; methodology.
This book uses R package, iForecast, to conduct financial economic time series forecasting with machine learning methods, especially the generation of dynamic forecasts out-of-sample.
This book provides a comprehensive examination of the structure of approximate optimal policies in Markov decision processes (MDPs) with finite state spaces, as well as approximate optimal solutions for deterministic discrete-time optimal control problems.
This book uses R package, iForecast, to conduct financial economic time series forecasting with machine learning methods, especially the generation of dynamic forecasts out-of-sample.
This book addresses the well-known capability and flexibility of classical and constructive semigroups (inherited from algebraic structures), to model, solve problems in extremely diverse situations, and develop interesting new algebraic ideas with many applications and connections to other areas of mathematics (logic, biomathematics, analysis, geometry, etc.
This book addresses the well-known capability and flexibility of classical and constructive semigroups (inherited from algebraic structures), to model, solve problems in extremely diverse situations, and develop interesting new algebraic ideas with many applications and connections to other areas of mathematics (logic, biomathematics, analysis, geometry, etc.
This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for computing parabolic partial differential equations (PDEs).
This book mainly provides readers with stochastic and statistical properties of conditional order statistics and conditional spacings as well as some stochastic properties of load-sharing systems.
This book mainly provides readers with stochastic and statistical properties of conditional order statistics and conditional spacings as well as some stochastic properties of load-sharing systems.
This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for computing parabolic partial differential equations (PDEs).
This book thoroughly explores the realm of data-driven blade-icing detection for wind turbines, focusing on multivariate time series classification to enhance the reliability and efficiency of wind energy utilization.
This book thoroughly explores the realm of data-driven blade-icing detection for wind turbines, focusing on multivariate time series classification to enhance the reliability and efficiency of wind energy utilization.
This book is useful not only for young but also for mature scientists who are preparing methods for studying natural environmental phenomena and their alteration by human activity.
This book is useful not only for young but also for mature scientists who are preparing methods for studying natural environmental phenomena and their alteration by human activity.
This book contains select chapters on a range of topics in directional statistics, multivariate statistical inference, financial statistics, statistical machine learning and reliability inference.
In today's manufacturing environment, managing inventories is one of the basic concerns of enterprises dealing with materials according to their activities.
This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists.
This book was inspired by years of questions asked by non-statistical professionals, from social scientists, public policy analysts, regulatory affairs specialists, engineers, and physical scientists.
This book examines the presence of stochastic and deterministic convergence in ten series of greenhouse gases, aerosol precursors, and aerosols across 29 industrialized and emerging countries from 1820 to 2018.
