Option Pricing with Monte Carlo Simulation — A Python library implementing Black–Scholes analytic pricing, Monte Carlo simulations (with variance reduction, quasi-MC), and advanced derivatives such as ...

We based our code primarily off of ikostrikov's pytorch-rl repo. Follow installation instructions there. @inproceedings{hendersonromoff2018optimizer, author = {Joshua Romoff and Peter Henderson and ...

Abstract: A variance reduction factor is defined to describe the rate of convergence and accuracy of spectra estimated from overlapping ultrasonic scattering volumes when the scattering is from a ...

Abstract: The Monte-Carlo (MC) technique is a traditional solution for a reliable statistical analysis, and in contrast to probabilistic methods, it can account for any complicate model. However, a ...

When I set out last summer to write a column about the insidious, margin-robbing problem of variance, I didn’t expect the first article to morph into a series of four, but in truth, it could go longer ...

Monte Carlo criticality simulations are widely used in nuclear safety demonstrations, as they offer an arbitrarily precise estimation of global and local tallies while making very few assumptions.

Introduction: Reconstruction time is still a restricting factor for PET but is commonly accelerated with the use of subsets. However, subset algorithms may demonstrate limit cycle behaviour that ...

When news breaks, you need to understand what actually matters. At Vox, our mission is to help you make sense of the world — and that work has never been more vital. But we can’t do it on our own. We ...