Monte Carlo and Quasi-Monte Carlo Methods

MCQMC 2020, Oxford, United Kingdom, August 10–14

Buch | Hardcover

XVI, 311 Seiten

2022 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-98318-5 (ISBN)

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This volume presents the revised papers of the 14th International Conference in Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing, MCQMC 2020, which took place online during August 10-14, 2020. This book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in statistics, machine learning, finance, and computer graphics, offering information on the latest developments in Monte Carlo and quasi-Monte Carlo methods and their randomized versions.

The MCQMC Conference Series.- The MCQMC Conference Series: P. L'Ecuyer and F. Puchhammer, Density Estimation by Monte Carlo and Quasi-Monte Carlo.- Sou-Cheng T. Choi, Fred J. Hickernell, Rathinavel Jagadeeswaran, Michael J. McCourt, and Aleksei G. Sorokin, Quasi-Monte Carlo Software.- Part II Regular Talks: P. L'Ecuyer, P. Marion, M. Godin, and F. Puchhamme, A Tool for Custom Construction of QMC and RQMC Point Sets.- Art B. Owen, On Dropping the first Sobol' Point.- C. Lemieux and J. Wiart, On the Distribution of Scrambled Nets over Unanchored Boxes.- S. Heinrich, Lower Bounds for the Number of Random Bits in Monte Carlo Algorithms.- N. Binder, S. Fricke, and A. Keller, Massively Parallel Path Space Filtering.- M. Hird, S. Livingstone, and G. Zanella, A fresh Take on 'Barker Dynamics' for MCMC.- P. Blondeel, P. Robbe, S. François, G. Lombaert and S. Vandewalle, On the Selection of Random Field Evaluation Points in the p-MLQMC Method.- S. Si, Chris. J. Oates, Andrew B. Duncan, L. Carin,and François-Xavier Briol, Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization.- Andrei S. Cozma and C. Reisinger, Simulation of Conditional Expectations under fast mean-reverting Stochastic Volatility Models.- M. Huber, Generating from the Strauss Process using stitching.- R. Nasdala and D. Potts, A Note on Transformed Fourier Systems for the Approximation of Non-Periodic Signals.- M. Hofert, A. Prasad, and Mu Zhu, Applications of Multivariate Quasi-Random Sampling with Neural Networks.- A. Keller and Matthijs Van keirsbilck, Artificial Neural Networks generated by Low Discrepancy Sequences.

Erscheinungsdatum	25.05.2022
Reihe/Serie	Springer Proceedings in Mathematics & Statistics
Zusatzinfo	XVI, 311 p. 69 illus., 53 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	651 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	Control variates • Density Estimation • light transport simulation • Low-discrepancy sequences • Markov chain Monte Carlo (MCMC) • MCQMC • Monte Carlo • Neural networks • quasi-Monte Carlo • quasi-Monte Carlo software • randomized algorithms • Sampling • Stochastic Simulation • variance reduction
ISBN-10	3-030-98318-8 / 3030983188
ISBN-13	978-3-030-98318-5 / 9783030983185
Zustand	Neuware