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<p>Part I Invited Articles: C. A. Beschle, A. Barth, Quasi Continuous Level Monte Carlo for Random Elliptic PDEs.- M. B. Giles, MLMC Techniques for Discontinuous Functions.- T. Helin, A. M. Stuart, A. L. Teckentrup, K. C. Zygalakis, Introduction to Gaussian Process Regression in Bayesian Inverse Problems, with new Results on Experimental Design for Weighted Error Measures.- V. Kaarnioja, Frances Y. Kuo, Ian H. Sloan, Lattice-Based Kernel Approximation and Serendipitous Weights for Parametric PDEs in Very High Dimensions.- E. Novak, Optimal Algorithms for Numerical Integration: Recent Results and Open Problems.- Chris. J. Oates, Minimum Kernel Discrepancy Estimators.- Gabriel Stoltz, Error Estimates and Variance Reduction for Nonequilibrium Stochastic Dynamics.- Part II Contributed Articles: F. Bernal, A. Berridi, Heuristics for the Probabilistic Solution of BVPs with Mixed Boundary Conditions.- Sou-Cheng T. Choi, Y. Ding, Fred J. Hickernell, J. Rathinavel, Aleksei G. Sorokin, Challenges in Developing Great Quasi-Monte Carlo Software.- L. Enzi, S. Thonhauser, Numerical Computation of Risk Functionals in PDMP Risk Models.- J. Fiedler, M. Gnewuch, Christian Weiß, New Bounds for the Extreme and the Star Discrepancy of Double-Infinite Matrices.- C. García-Pareja, F. Nobile, Unbiased Likelihood Estimation of Wright-Fisher Diffusion Processes.- Alexander D. Gilbert, Frances Y. Kuo, Ian H. Sloan, A. Srikumar, Theory and Construction of Quasi-Monte Carlo Rules for Asian Option Pricing and Density Estimation.- Philipp A. Guth, V. Kaarnioja, Application of Dimension Truncation Error Analysis to High Dimensional Function Approximation in Uncertainty Quantification.- Rami El Haddad, C. Lécot, Pierre L’Ecuyer, Simple Stratified Sampling for Simulating Multi-Dimensional Markov Chains.-&nbsp;K. Harsha, M. Gnewuch, M. Wnuk, Infinite-Variate 𝐿2-Approximation with Nested Subspace Sampling.- S. Heinrich, Randomized Complexity of Vector-Valued Approximation.-&nbsp;<br>
A. Keller, C. Wächter, N. Binder, Quasi-Monte Carlo Algorithms (not only) for Graphics Software.- S. Krumscheid, Per Pettersson, Sequential Estimation using Hierarchically Stratified Domains with Latin Hypercube Sampling.- Frances Y. Kuo, Weiwen Mo, D. Nuyens, Ian H. Sloan, A. Srikumar, Comparison of Two Search Criteria for Lattice-based Kernel Approximation.- M. Longo, C. Schwab, A. Stein, A-posteriori QMC-FEM Error Estimation for Bayesian Inversion and Optimal Control with Entropic Risk Measure.- E. Løvbak, F. Blondeel, A. Lee, L. Vanroye, Andreas Van Barel, G. Samaey, Reversible Random Number Generation for Adjoint Monte Carlo Simulation of the Heat Equation.- H. Maatouk, D. Rullière, X. Bay, Large Scale Gaussian Processes with Matheron’s Update Rule and Karhunen-Loève Expansion.- A. Mickel, A. Neuenkirch, The Order Barrier for the 𝐿1-approximation of the Log-Heston SDE at a Single Point.- D. Nuyens, L. Wilkes, A Randomised Lattice Rule Algorithm with Pre-determined Generating Vector and Random Number of Points for Korobov Spaces with 0 &lt; 𝛼 ≤ 1/2.- L. Paulin, D. Coeurjolly, N. Bonneel, Jean-Claude Iehl, V. Ostromoukhov, A. Keller, Generator Matrices by Solving Integer Linear Programs.- K. Ravi, T. Neckel, Hans-Joachim Bungartz, Multi-fidelity No-U-Turn Sampling.- C. Reisinger, M. Olympia Tsianni, Convergence of the Euler–Maruyama Particle Scheme for a Regularised McKean–Vlasov Equation Arising from the Calibration of Local-stochastic Volatility models.- A. G. Sorokin, J. Rathinavel, On Bounding and Approximating Functions of Multiple Expectations using Quasi-Monte Carlo.- K. Spendier, M. Szölgyenyi, Convergence of the Tamed-Euler–Maruyama Method for SDEs with Discontinuous and Polynomially Growing Drift.- Víctor de la Torre, J. Marzo, QMC Strength for some Random Configurations on the Sphere.- P. Vanmechelen, G. Lombaert, G. Samaey, Multilevel MCMC with Level-Dependent Data in a Model Case of Structural Damage Assessment.- M. Wnuk, A Note on Compact Embeddings of Reproducing Kernel Hilbert Spaces in 𝐿2 and Infinite-variate Function Approximation.</p>

This book presents the refereed proceedings of the 15th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held in Linz, Austria, and organized by the Johannes Kepler University Linz and the Austrian&nbsp;Academy of Sciences, in July 2022. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these highly active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, in particular arising in finance, statistics and computer graphics.<div><br></div>

Recent advances on Monte Carlo (MC) methods and their application Prime source of information on quasi-Monte Carlo (QMC) methods and their randomized versions Covers applications of MC and QMC in statistics, automatic learning, finance, physics, partial differential equations, etc