We survey some of the recent developments on quasi-Monte Carlo (QMC) methods, which,
in their basic form, are a deterministic counterpart to the Monte Carlo (MC) method. Our main …

This paper is a contemporary review of QMC ('quasi-Monte Carlo') methods, that is, equal-
weight rules for the approximate evaluation of high-dimensional integrals over the unit cube …

Planning algorithms are impacting technical disciplines and industries around the world,
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …

Multivariate normal and t probabilities are needed for statistical inference in many
applications. Modern statistical computation packages provide functions for the computation …

Quasi–Monte Carlo methods have become an increasingly popular alternative to Monte
Carlo methods over the last two decades. Their successful implementation on practical …

We present, implement, and analyze a spectrum of closely-related planners, designed to
gain insight into the relationship between classical grid search and probabilistic roadmaps …

At the nanoscale, no circuit parameters are truly deterministic; most quantities of practical
interest present themselves as probability distributions. Thus, Monte Carlo techniques …

Good lattice point sets are an important kind of low discrepancy points for multidimensional
quadrature, simulation, experimental design, etc. The theoretical development of lattice point …

In this paper, we discuss the field of sampling-based motion planning. In contrast to methods
that construct boundary representations of configuration space obstacles, samplingbased …

Previous conjoint choice design construction procedures have produced a single
homogeneous design that is administered to all study participants. In contrast, this article …