The main objective of this work is to develop a detailed step-by-step guide to the development and application of a new class of efficient Monte Carlo methods to solve practically important problems faced by insurers under ...

- In this book, the authors expand their excellent coverage of the tools macroeconomists use to solve, evaluate, and estimate models. Linear and nonlinear solution methods are crefully described and help the reader easily ...

- In this book, the authors expand their excellent coverage of the tools macroeconomists use to solve, evaluate, and estimate models. Linear and nonlinear solution methods are crefully described and help the reader easily ...

Nessa tese é introduzido um novo paradigma de aprendizagem de parâmetros sequencial em modelos de Markov ocultos, capaz de acomodar vários outros algoritmos encontrados na literatura como casos particulares. Essa generalidade ...

In this work, a novel sequential Monte Carlo filter is introduced which aims at an efficient sampling of the state space. Particles are pushed forward from the prediction to the posterior density using a sequence of mappings ...

Recently, some works have suggested methods to combine variational probabilistic inference with Monte Carlo sampling. One promising approach is via local optimal transport. In this approach, a gradient steepest descent ...

This paper analyses and compares the performance of a number of approaches implemented for the detection of capacity regeneration phenomena (measured in ampere-hours) in the degradation trend of energy storage devices, ...