Sequential Monte Carlo in python
-
Updated
Oct 14, 2024 - Python
Sequential Monte Carlo in python
Samplin' Safari is a research tool to visualize and interactively inspect high-dimensional (quasi) Monte Carlo samplers.
Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
generation of Sobol low-discrepancy sequence (LDS) for the Julia language
Robust estimations from distribution structures: III. Non-asymptotic
Quasi-Monte-Carlo numerical computation of multivariate normal probabilities
(t, m, s)-nets generator / Генератор (t, m, s)-сетей
R package with quasi-Monte Carlo methods to estimate mixed models commonly used for random effect structures from pedigrees.
A simple quasi-random number generator implemented in C++ for generating low discrepancy sequences in any number of dimensions.
The aim of this project is to compare different pricing methods for an Asian option. Comparisons will be made in terms of MSE, CPU time and (empirical) variance of estimators.
Fast construction of Gaussian Process Regression models supporting gradient information.
This repository contains the source code for my MSc Project on "Scalable Inference for Generative Models using Quasi-Monte Carlo" at the Department of Statistical Science, UCL.
Final assessment for "Monte Carlo methods and sampling for computing course" within the PhD program in Information Engineering of the Department of Information Engineering @ University of Pisa, A.A. 2022/2023
Code of the paper The Robust Randomized Quasi Monte Carlo method, applications to integrating singular functions by E. Gobet M. Lerasle and D. Métivier
MonteCarlo and Quasi-MonteCarlo methods for the valuations of spread and lookback finantial options.
Some randomization methods for Randomized Quasi Monte Carlo e.g. scrambling, shift
Quasi-Monte Carlo Sequence Generators in OpenCL and C
Add a description, image, and links to the quasi-monte-carlo topic page so that developers can more easily learn about it.
To associate your repository with the quasi-monte-carlo topic, visit your repo's landing page and select "manage topics."