There are 2 repositories under monte topic.
Bootstrap and Monte Carlo Hypothesis Testing with R
A library for creating and verifying orthogonal arrays for Monte Carlo sampling
A physically based offline renderer
A visualization framework for D3.js and SVG. Ships with prebuilt charts and components.
Simplest implimentation of D-dimensional classical Ising model in Julia.
Monte Carlo + Heat transfer for modelling laser tissue abaltion
TOPAS-nBio extension repository, for documentation and license see: https://topas-nbio.readthedocs.io/
Monte Carlo Penalty Selection for graphical lasso
Value at Risk (VaR) and Sharpe Ratio computations of securities on the Australian Stock Exchange (ASX).
A weapon simulator for the video game Warframe.
The source/figures/etc for my Bachelor's thesis
When working with converters, precision is important, and it's known that commercial resistors tend to vary in their resistors values. This code is a tool based on the Monte Carlo algorithm to analise how adequate the chosen tolerance is to your project.
Estimating Pi using the Monte Carlo Method. Written in C# + Windows Forms App
Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression
Simulations coded in Python of the proposed problems in the book Introduction to Probability by Grinstead and Snell.
MCTS algorithm with MC-RAVE
The continuous integration testsuite for TOPAS-nBio
An extension that eases use of d3-tip with Monte.
Plotting and convenience scripts for post-processing various Monte Python MCMC runs (MH, CH, NS, PC).
Simulating games of Monopoly.
Analog circuits for a Spiking Neuron (and Synapse) in CMOS 180 nm, Cadence ADE XL (Monte Carlo) and ADE_L (Nominal) simulations.
An example of the Monte Carlo method of Pi approximation written in Intel x86_64.
Approximating PI number using the Monte Carlo Method + visualisation in C#
Approximating PI number using the Monte Carlo Method + visualisation in C#, web version
Integrate using Monte Carlo Method (and visualize)
Running Monte Carlo - Markov Chain algorithm on synthesized spectral models made by CLOUDY to compare them with data from CECILIA survey