Tabla de Contenidos: “…Message creationInference with approximate messages; Sum-product expectation propagation; Belief update propagation; Sampling-based approximate methods; Forward sampling; Conditional probability distribution; Likelihood weighting and importance sampling; Importance sampling; Importance sampling in Bayesian networks; Computing marginal probabilities; Ratio likelihood weighting; Normalized likelihood weighting; Markov chain Monte Carlo methods; Gibbs sampling; Markov chains; The multiple transitioning model; Using a Markov chain; Collapsed particles; Collapsed importance sampling; Summary…”

Tabla de Contenidos: “…MEASUREMENT AS REDUCTION IN UNCERTAINTYMEASUREMENT AS EXPRESSIONS OF UNCERTAINTY; BUT WE DON'T HAVE ENOUGH DATA...AND NEITHER DOES ANYONE ELSE; CALIBRATION; EQUIVALENT BET TEST; Chapter 6 - Analysis Process; THE TOOLS NECESSARY TO APPLY THE FAIR RISK MODEL; HOW TO APPLY THE FAIR RISK MODEL; PROCESS FLOW; SCENARIO BUILDING; THE ANALYSIS SCOPE; EXPERT ESTIMATION AND PERT; MONTE CARLO ENGINE; LEVELS OF ABSTRACTION; Chapter 7 - Interpreting Results; WHAT DO THESE NUMBERS MEAN? …”

Tabla de Contenidos: “…Execution-Time Software Reliability ModelsSoftware Reliability Prediction Tools Prior to Testing; References; 4 Reliability Models; Introduction; Reliability Block Diagram: System Modeling; Example of System Reliability Models Using RBDs; Reliability Growth Model; Similarity Analysis and Categories of a Physical Model; Monte Carlo Models; Markov Models; References; 5 Design Failure Modes, Effects, and Criticality Analysis; Introduction to FMEA and FMECA; Design FMECA; Principles of FMECA-MA; Design FMECA Approaches; Example of a Design FMECA Process; Risk Priority Number; Final Thoughts…”

Tabla de Contenidos: “…COMMERCIAL LOAN SYNDICATIONSUMMARY; QUESTIONS; CHAPTER 8 Credit Risk Mitigation; OVERVIEW; INSURANCE CONTRACTS; CREDIT DERIVATIVES AND RISK MITIGATION; CREDIT DEFAULT SWAP MECHANICS; CREDIT-LINKED NOTE MECHANICS; COLLATERALIZED DEBT OBLIGATION MECHANICS; CREDIT HEDGING OUTCOMES; SUMMARY; QUESTIONS; CHAPTER 9 Interest Rate Risk; OVERVIEW OF SIFIBANK'S INTEREST RATE RISK EXPOSURE; Duration Models; Extensions of the Duration Model; PRINCIPAL COMPONENTS ANALYSIS; ANALYTIC VAR MEASUREMENT OF INTEREST RATE RISK; MONTE CARLO VAR INTEREST RATE RISK METHODS…”

Tabla de Contenidos:

Tabla de Contenidos: “…Risk Model Implementation-Step by StepRisk Model Implementation Checklists; Further Risk Models and Implementation Details from Historical to Parametric and Monte Carlo Based Approaches; Chapter 8: Introducing Performance Measurement; The Role of Performance Measurement; Performance Measurement; Performance Attribution; Performance Using Risk Adjusted Return on Capital; Investment Performance Management; Chapter 9: Implementing Performance Models; Performance Measurement Implementation: Step by Step; Performance Measurement Implementation Checklists; Further Performance Measurement Models…”

Tabla de Contenidos: “…Physics -- Gravitational Wave Signals from Simulations of Black Hole Dynamics -- The SuperN-Project: Understanding Core Collapse Supernovae -- MHD Code Optimizations and Jets in Dense Gaseous Halos -- Anomalous Water Optical Absorption: Large-Scale First-Principles Simulations -- The Electronic Structures of Nanosystems: Calculating the Ground States of Sodium Nanoclusters and the Actuation of Carbon Nanotubes -- Object-Oriented SPH-Simulations with Surface Tension -- Simulations of Particle Suspensions at the Institute for Computational Physics -- Solid State Physics -- Nano-Systems in External Fields and Reduced Geometry: Numerical Investigations -- Signal Transport and Finite Bias Conductance in and Through Correlated Nanostructures -- Atomistic Simulations of Dislocation — Crack Interaction -- Monte Carlo Simulations of Strongly Correlated and Frustrated Quantum Systems -- Chemistry -- Characterization of Catalyst Surfaces by STM Image Calculations -- Theoretical Investigation of the Self-Diffusion on Au(100) -- TrpAQP: Computer Simulations to Determine the Selectivity of Aquaporins -- Computational Fluid Dynamics -- Direct Numerical Simulation and Analysis of the Flow Field Around a Swept Laminar Separation Bubble -- Direct Numerical Simulation of Primary Breakup Phenomena in Liquid Sheets -- Direct Numerical Simulation of Mixing and Chemical Reactions in a Round Jet into a Crossflow — a Benchmark -- Numerical Simulation of the Bursting of a Laminar Separation Bubble -- Parallel Large Eddy Simulation with UG -- LES and DNS of Melt Flow and Heat Transfer in Czochralski Crystal Growth -- Efficient Implementation of Nonlinear Deconvolution Methods for Implicit Large-Eddy Simulation -- Large-Eddy Simulation of Tundish Flow -- Large Eddy Simulation of Open-Channel Flow Over Spheres -- Prediction of the Resonance Characteristics of Combustion Chambers on the Basis of Large-Eddy Simulation -- Investigations of Flow and Species Transport in Packed Beds by Lattice Boltzmann Simulations -- Rheological Properties of Binary and Ternary Amphiphilic Fluid Mixtures -- The Effects of Vortex Generator Arrays on Heat Transfer and Flow Field -- Investigation of the Influence of the Inlet Geometry on the Flow in a Swirl Burner -- Numerical Investigation and Simulation of Transition Effects in Hypersonic Intake Flows -- Aeroelastic Simulations of Isolated Rotors Using Weak Fluid-Structure Coupling -- Computational Study of the Aeroelastic Equilibrium Configuration of a Swept Wind Tunnel Wing Model in Subsonic Flow -- Structural Mechanics -- Numerical Prediction of the Residual Stress State after Shot Peening -- Computer-Aided Destruction of Complex Structures by Blasting -- Wave Propagation in Automotive Structures Induced by Impact Events -- Miscellaneous Topics -- Continental Growth and Thermal Convection in the Earth’s Mantle -- Efficient Satellite Based Geopotential Recovery -- Molecular Modeling of Hydrogen Bonding Fluids: Monomethylamine, Dimethylamine, and Water Revised -- The Application of a Black-Box Solver with Error Estimate to Different Systems of PDEs -- Scalable Parallel Suffix Array Construction…”

Tabla de Contenidos: “…Thermodynamic Basis of Phase Transformations; 2.1 Reversible and Irreversible Thermodynamics; 2.2 Solution Thermodynamics; Chapter 3. Monte Carlo Potts Model; 3.1 Introduction; 3.2 Two-State Potts Model (Ising Model); 3.3 Q-State Potts Model; 3.4 Speed-Up Algorithms…”

Tabla de Contenidos: “…Statistics Basics; 3.1 Basic Concepts; 3.2 Markov Chain Monte Carlo; 3.3 The Normal Distribution; Chapter 4. …”

Tabla de Contenidos: “…; Gordon Moore and Endless Innovation; Potential Pitfall: Unrealistic Expectations; Chapter 6: Getting That Cash Flow; Potential Pitfall-The All High-Dividend Portfolio; Homegrown Dividends; How Much Do You Need?; The 10% Myth; Monte Carlo-Not Just a Casino; Let''s Get Bootstrapping; Chapter 7: Can I Get There?…”

Tabla de Contenidos: “…Chapter 18: Context Steering : Behavior-Driven Steering at the Macro ScaleChapter 19: Guide to Anticipatory Collision Avoidance; Chapter 20: Hierarchical Architecture for Group Navigation Behaviors; Chapter 21: Dynamic Obstacle Navigation in Fuse; Chapter 22: Introduction to Search for Games; Chapter 23: Personality Reinforced Search for Mobile Strategy Games; Chapter 24: Interest Search : A Faster Minimax; Chapter 25: Monte Carlo Tree Search and Related Algorithms for Games; Chapter 26: Rolling Your Own Finite-Domain Constraint Solver…”

Tabla de Contenidos: “…Response PlanningReporting; Implementation; Review; Post-Project Review; Conclusion; Chapter 15: Simulating Possible Futures (Quantitative Analysis); Introducing Monte Carlo Analysis; Quantitative Risk Analysis in the Project Life Cycle; Quantitative Risk Analysis in the ATOM Process; Getting Started; Analysis; Interpreting Outputs; Using Results; Conclusion; Chapter 16: Managing Risk in Programs; From Projects to Programs; Program Management Basics; Aim and Scope of Program Risk Management; Managing Program Risk; Epilogue: Next Steps; Step 1: Appoint an Organizational Risk Sponsor…”

Tabla de Contenidos: “…Node Parallelism for Graph Centrality Metrics 3 Optimizing parallel prefix operations for the Fermi architecture 4 Building an Efficient Hash Table on the GPU 5 An Efficient CUDA Algorithm for the Maximum Network Flow Problem 6 On Improved Memory Access Patterns for Cellular Automata Using CUDA 7 Fast Minimum Spanning Tree Computation on Large Graphs 8 Fast in-place sorting with CUDA based on bitonic sort Part 2: Numerical Algorithms - Frank Jargstorff, NVIDIA 9 Interval Arithmetic in CUDA 10 Approximating the erfinv Function 11 A Hybrid Method for Solving Tridiagonal Systems on the GPU 12 LU Decomposition in CULA 13 GPU Accelerated Derivative-free Optimization Part 3: Engineering Simulation - Peng Wang, NVIDIA 14 Large-scale gas turbine simulations on GPU clusters 15 GPU acceleration of rarefied gas dynamic simulations 16 Assembly of Finite Element Methods on Graphics Processors 17 CUDA implementation of Vertex-Centered, Finite Volume CFD methods on Unstructured Grids with Flow Control Applications 18 Solving Wave Equations on Unstructured Geometries 19 Fast electromagnetic integral equation solvers on graphics processing units (GPUs) Part 4: Interactive Physics for Games and Engineering Simulation - Richard Tonge, NVIDIA 20 Solving Large Multi-Body Dynamics Problems on the GPU 21 Implicit FEM Solver in CUDA 22 Real-time Adaptive GPU multi-agent path planning Part 5: Computational Finance - Thomas Bradley, NVIDIA 23 High performance finite difference PDE solvers on GPUs for financial option pricing 24 Identifying and Mitigating Credit Risk using Large-scale Economic Capital Simulations 25 Financial Market Value-at-Risk Estimation using the Monte Carlo Method Part 6: Programming Tools and Techniques - Cliff Wooley, NVIDIA 26 Thrust: A Productivity-Oriented Library for CUDA 27 GPU Scripting and Code Generation with PyCUDA 28 Jacket: GPU Powered MATLAB Acceleration 29 Accelerating Development and Execution Speed with Just In Time GPU Code Generation 30 GPU Application Development, Debugging, and Performance Tuning with GPU Ocelot 31 Abstraction for AoS and SoA Layout in C++ 32 Processing Device Arrays with C++ Metaprogramming 33 GPU Metaprogramming: A Case Study in Biologically-Inspired Machine Vision 34 A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs 35 Dynamic Load Balancing using Work-Stealing 36 Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads…”

“…The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. …”

Tabla de Contenidos: “…Towards a better estimation of the global energy efficiency market 24 -Summary 24 -Energy Efficiency Market Report 2014: Approach to evaluating the energy efficiency market 24 -Savings generated by energy efficiency: The market’s output 25 -Energy efficiency: Still the first fuel 26 -Estimating investment in the energy efficiency market 28 --Method 1: Estimate using gross capital formation 29 --Method 2: Estimate based on changes in energy intensity30 --Method 3: Estimate based on the Long-term Industrial Energy Forecast (LIEF) model 31 --Method 4: Estimate based on a Monte Carlo simulation 31 --Method 5: Estimate based on leveraging 32 --Method 6: Estimate based on the World Energy Investment Outlook 33 -Conclusion: Towards improved market valuations 33 -References 34 2. …”

Tabla de Contenidos: “…Financial Modeling with Crystal Ball and Excel; Contents; Preface; Acknowledgments; About the Author; CHAPTER 1 Introduction; 1.1 FINANCIAL MODELING; 1.2 RISK ANALYSIS; 1.3 MONTE CARLO SIMULATION; 1.4 RISK MANAGEMENT; 1.5 BENEFITS AND LIMITATIONS OF USING CRYSTAL BALL; 1.5.1 Benefits; 1.5.2 Limitations; CHAPTER 2 Analyzing Crystal Ball Forecasts; 2.1 SIMULATING A 50-50 PORTFOLIO; 2.1.1 Accumulate.xls; 2.1.2 Frequency Chart; 2.1.3 Cumulative Frequency Chart; 2.1.4 Statistics View; 2.1.5 Forecast Window Percentiles View; 2.2 VARYING THE ALLOCATIONS; 2.2.1 Decision Table Tool; 2.2.2 Trend Chart…”

Tabla de Contenidos: “…Generator outputs of StackedGAN -- Conclusion -- Reference -- Chapter 7: Cross-Domain GANs -- Principles of CycleGAN -- The CycleGAN Model -- Implementing CycleGAN using Keras -- Generator outputs of CycleGAN -- CycleGAN on MNIST and SVHN datasets -- Conclusion -- References -- Chapter 8: Variational Autoencoders (VAEs) -- Principles of VAEs -- Variational inference -- Core equation -- Optimization -- Reparameterization trick -- Decoder testing -- VAEs in Keras -- Using CNNs for VAEs -- Conditional VAE (CVAE) -- -VAE: VAE with disentangled latent representations -- Conclusion -- References -- Chapter 9: Deep Reinforcement Learning -- Principles of reinforcement learning (RL) -- The Q value -- Q-Learning example -- Q-Learning in Python -- Nondeterministic environment -- Temporal-difference learning -- Q-Learning on OpenAI gym -- Deep Q-Network (DQN) -- DQN on Keras -- Double Q-Learning (DDQN) -- Conclusion -- References -- Chapter 10: Policy Gradient Methods -- Policy gradient theorem -- Monte Carlo policy gradient (REINFORCE) method -- REINFORCE with baseline method -- Actor-Critic method -- Advantage Actor-Critic (A2C) method -- Policy Gradient methods with Keras -- Performance evaluation of policy gradient methods -- Conclusion -- References -- Other Books You May Enjoy -- Index…”

Tabla de Contenidos: “…Setting up PyPy -- Running a particle simulator in PyPy -- Other interesting projects -- Summary -- Chapter 6: Implementing Concurrency -- Asynchronous programming -- Waiting for I/O -- Concurrency -- Callbacks -- Futures -- Event loops -- The asyncio framework -- Coroutines -- Converting blocking code into non-blocking code -- Reactive programming -- Observables -- Useful operators -- Hot and cold observables -- Building a CPU monitor -- Summary -- Chapter 7: Parallel Processing -- Introduction to parallel programming -- Graphic processing units -- Using multiple processes -- The Process and Pool classes -- The Executor interface -- Monte Carlo approximation of pi -- Synchronization and locks -- Parallel Cython with OpenMP -- Automatic parallelism -- Getting started with Theano -- Profiling Theano -- Tensorflow -- Running code on a GPU -- Summary -- Chapter 8: Distributed Processing -- Introduction to distributed computing -- An introduction to MapReduce -- Dask -- Directed Acyclic Graphs -- Dask arrays -- Dask Bag and DataFrame -- Dask distributed -- Manual cluster setup -- Using PySpark -- Setting up Spark and PySpark -- Spark architecture -- Resilient Distributed Datasets -- Spark DataFrame -- Scientific computing with mpi4py -- Summary -- Chapter 9: Designing for High Performance -- Choosing a suitable strategy -- Generic applications -- Numerical code -- Big data -- Organizing your source code -- Isolation, virtual environments, and containers -- Using conda environments -- Virtualization and Containers -- Creating docker images -- Continuous integration -- Summary -- Index…”

Tabla de Contenidos: “…Environmental ImpactHumidity; Conductivity; Temperature; Model and simulation; Model Geometries; Stripline structures; Microstrip structures; Corner Models; Iterative corner model; Monte Carlo corner model; Ideal Assumptions: Homogeneous Impedance; Ideal Assumptions: Crosstalk Aggressors; Transmitters; IBIS Models; Spice Voltage Source Model; Linearity test; 3D Modeling; Ports/Terminals; Wave ports; Lumped ports; Model Analysis Settings; Discrete or interpolating solutions; Frequency range and step size; Port order; Normalize result to 50ohms; Plated-Through-Hole Via; Model Techniques…”

Tabla de Contenidos: “…2.8.2 Resolution and error2.8.3 Uncertainty in measurement; 2.8.3.1 The propagation of probability distributions; 2.8.3.2 The GUM uncertainty framework; 2.8.3.3 A Monte Carlo method; 2.9 The laser; 2.9.1 Theory of the helium-neon laser; 2.9.2 Single-mode laser wavelength stabilisation schemes; 2.9.3 Laser frequency stabilisation using saturated absorption; 2.9.3.1 Two-mode stabilisation; 2.9.4 Zeeman-stabilised 633nm lasers; 2.9.5 Frequency calibration of a (stabilised) 633nm laser; 2.9.6 Modern and future laser frequency standards; References…”