Procedural noise is a fundamental tool in Computer Graphics. However, designing noise patterns is hard. In this paper, we present Gabor noise by example, a method to estimate the ...
Bruno Galerne, Ares Lagae, Sylvain Lefebvre, Georg...
Importance sampling is a popular approach to estimate rare event failures of SRAM cells. We propose to improve importance sampling by probability collectives. First, we use “Kul...
Fang Gong, Sina Basir-Kazeruni, Lara Dolecek, Lei ...
Consider the problem of estimating the small probability that the maximum of a random walk exceeds a large threshold, when the process has a negative drift and the underlying rand...
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
Monte Carlo simulation techniques that use function approximations have been successfully applied to approximately price multi-dimensional American options. However, for many pric...
In this paper we introduce Refractor Importance Sampling (RIS), an improvement to reduce error variance in Bayesian network importance sampling propagation under evidential reason...
The paper introduces an AND/OR importance sampling scheme for probabilistic graphical models. In contrast to conventional importance sampling, AND/OR importance sampling caches sa...
We investigate the use of Antithetic Variables, Control Variates and Importance Sampling to reduce the statistical errors of option sensitivities calculated with the Likelihood Ra...