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Catalogue complet

Spielmann R: Theoretical Fluid Mechanics

Theoretical Fluid Mechanics

An application-oriented introduction with detailed derivations

Fluidization Processes - Design and Operation

Series in Computational Biophysics

Multiscale methods are ideally suited to simulate the processes at work in many biomolecular systems, which often span a large range of time and length scales. Multiscale Methods in Molecular Biophysics highlights the advantages of these methods for integrating different levels of detail in a single simulation setting. It covers the practical methodology and successful applications in areas such as enzyme catalysis, protein folding, and ligand binding. The book is divided into three main sections: combination quantum and classical (atomistic) descriptions, approaches that combine atomistic and coarse-grained level of details, and multiscale methods where the resolution coupling is between global collective coordinates and local details.

Multiscale methods are ideally suited to simulate the processes at work in many biomolecular systems, which often span a large range of time and length scales. Multiscale Methods in Molecular Biophysics highlights the advantages of these methods for integrating different levels of detail in a single simulation setting. It covers the practical methodology and successful applications in areas such as enzyme catalysis, protein folding, and ligand binding. The book is divided into three main sections: combination quantum and classical (atomistic) descriptions, approaches that combine atomistic and coarse-grained level of details, and multiscale methods where the resolution coupling is between global collective coordinates and local details.

Multiscale Methods in Molecular Biophysics

Quantitative Biology

Radon Series on Computational and Applied Mathematics

Hilbert Space Methods for the Theory of Electromagnetism

Maxwell’s Equations

While the field of Deep Learning has been advancing at frightening speeds during the last ten years, we do not have a plausible theoretical explanation of its success yet. One can safely say that Deep Learning works, but nobody really understands why. Nevertheless, starting around five years before now, a decent number of theoretical papers specifically concerning neural nets started to emerge at top machine learning venues. This makes us think that the core of Deep Learning theory has already started to crystallize.The goal of the present book is to present these core concepts of Deep Learning theory to readers so that they could directly dive into recent papers of this area. For this purpose, each chapter elaborates a simple model or a classical result in details first and then discusses possible generalizations and more recent developments of the same idea.We have to warn the reader that the present book is not a mathematical manuscript. Not all results here are stated as formal theorems and not all theorems are provided with complete and rigorous proofs. Many of the theorems of the book are proven up to some technical lemmas, while for some there is only a proof sketch. This conforms with the main idea of the book: present and illustrate concepts rather than reproduce all the results.The book, in its present form, covers the following topics: uniform generalization bounds, PAC-bayesian generalization bounds, double descent phenomena, infinitely-wide networks, implicit bias of gradient descent, loss landscape, gradient descent convergence guarantees, and initialization strategies.

Elements Of Deep Learning Theory

Storytelling with Data Box Set

Dynamics and Astrophysics of Galaxies

Originating from the lattice Gas Automaton, LBM has reshaped the field with its straightforward approach and high efficacy. Despite its widespread use, navigating the scattered literature can be daunting for newcomers. Fluid Dynamics with the Lattice Boltzmann Method presents a clear path from novice to expert. This comprehensive guide bridges gaps in understanding, covering essential principles and exploring advanced topics like compressible flows and combustion. Authored by experts, this book consolidates diverse models and recent advancements, ensuring you're equipped to navigate the latest developments in computational fluid dynamics. Whether you're just starting out or aiming to stay ahead of the curve, this book is your essential companion in mastering LBM.

Fluid Dynamics with the Lattice Boltzmann Method

This volume provides a comprehensive introduction to computational materials science, focusing on both fundamental theory and practical applications. The book serves as an essential resource for the researchers working at the intersection of materials science and practical computational techniques. The authors present an in-depth examination of the theoretical principles that govern the behaviour and properties of materials in the context of computational analysis, providing a strong connection to the research areas of quantum mechanics, statistical mechanics, and thermodynamics. The book serves as a platform for the materials community interested in the transition to computational methodologies, detailing state-of-the-art simulation and modelling techniques like density functional theory, molecular dynamics, and finite element analysis.<ul><li>Provides an overview of recent advances in computational material science related to its energy, environment and health;</li><li>Focuses on commercial applications with case studies and practical examples of this work addressing current challenges;</li><li>Brings together a diverse range of perspectives and disciplines from a global slate of experts.</li></ul>

This volume provides a comprehensive introduction to computational materials science, focusing on both fundamental theory and practical applications. The book serves as an essential resource for the researchers working at the intersection of materials science and practical computational techniques. The authors present an in-depth examination of the theoretical principles that govern the behaviour and properties of materials in the context of computational analysis, providing a strong connection to the research areas of quantum mechanics, statistical mechanics, and thermodynamics. The book serves as a platform for the materials community interested in the transition to computational methodologies, detailing state-of-the-art simulation and modelling techniques like density functional theory, molecular dynamics, and finite element analysis.

Theoretical and Computational Materials Science: Advances and Applications

Woodhead Publishing Series in Civil and Structural Engineering

Advanced Tools for Monitoring, Mitigation, and Lifecycle Optimization

Climate Change Effects on Infrastructure

Selected Topics

Quantum Modelling of Economic and Financial Systems

The Navier-Stokes equations - modeling the motion of viscous, incompressible Newtonian fluids - have been capturing the attention of an increasing number of mathematicians over the years and has now become one of the most intensely studied subjects in applied analysis. This project is dedicated to a complete and updated mathematical analysis of fundamental topics related to these equations. Every subject will be analyzed using different approaches. The main ideas behind them as well as their differences will also be emphasized and discussed. The book aims at being self-contained, however, it will also be supported by a vast bibliography for further reading.

Navier-Stokes Equations: A Mathematical Analysis

Theoretical Fluid Mechanics

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