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Multifidelity importance sampling [PDF]
Computer Methods in Applied Mechanics and Engineering, 2016 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Peherstorfer, Benjamin +3 more
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Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation
Frontiers in Big Data, 2022 Despite progress toward gender equality in the labor market over the past few decades, gender segregation in labor force composition and labor market outcomes persists.
Shenggang Hu +11 more
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, 2023 Fixed a few typos and errors, and added a real data ...
Datta, Jyotishka, Polson, Nicholas G.
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Steerable Importance Sampling [PDF]
2007 IEEE Symposium on Interactive Ray Tracing, 2007 We present an algorithm for efficient stratified importance sampling of environment maps that generates samples in the positive hemisphere defined by local orientation of arbitrary surfaces while accounting for cosine weighting. The importance function is dynamically adjusted according to the surface normal using steerable basis functions.
Kartic Subr, James Arvo
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Importance Sampling for Dispersion-managed Solitons [PDF]
, 2010 The dispersion-managed nonlinear Schrödinger (DMNLS) equation governs the long-term dynamics of systems which are subject to large and rapid dispersion variations.
Biondini, Gino, Spiller, Elaine T.
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Statistics and Computing, 2001 Simulated annealing - moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions - has traditionally been used as an inexact method of handling isolated modes in Markov chain samplers. Here, it is shown how one can use the Markov chain transitions for such an annealing sequence to define an ...
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Unconstrained recursive importance sampling
The Annals of Applied Probability, 2010 We propose an unconstrained stochastic approximation method of finding the optimal measure change (in an a priori parametric family) for Monte Carlo simulations. We consider different parametric families based on the Girsanov theorem and the Esscher transform (or exponential-tilting).
Lemaire, Vincent, Pagès, Gilles
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A Bayesian Spatial Model to Predict Disease Status Using Imaging Data From Various Modalities
Frontiers in Neuroscience, 2018 Relating disease status to imaging data stands to increase the clinical significance of neuroimaging studies. Many neurological and psychiatric disorders involve complex, systems-level alterations that manifest in functional and structural properties of ...
Wenqiong Xue +2 more
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Simulation of diffusions by means of importance sampling paradigm [PDF]
, 2009 The aim of this paper is to introduce a new Monte Carlo method based on importance sampling techniques for the simulation of stochastic differential equations.
Antoine Lejay +2 more
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EXACT SIMULATION OF A BOOLEAN MODEL
Image Analysis and Stereology, 2013 A Boolean model is a union of independent objects (compact random subsets) located at Poisson points. Two algorithms are proposed for simulating a Boolean model in a bounded domain. The first one applies only to stationary models.
Christian Lantuéjoul
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