Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.

Samplin' Safari is a research tool to visualize and interactively inspect high-dimensional (quasi) Monte Carlo samplers.

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

A Toolkit for Distributional Control of Generative Models

David Mackay's book review and problem solvings and own python codes, mathematica files

My solutions to Yandex Practical Reinforcement Learning course in PyTorch and Tensorflow

Robust estimations from distribution structures: III. Non-asymptotic

[AAAI20] TensorFlow implementation of the Collaborative Sampling in Generative Adversarial Networks

pMoSS (p-value Model using the Sample Size) is a Python code to model the p-value as an n-dependent function using Monte Carlo cross-validation. Exploits the dependence on the sample size to characterize the differences among groups of large datasets

Codebase for "Greedy Shapley Client Selection for Communication-Efficient Federated Learning"

feyntrop integrates Feynman graphs using tropical sampling

Accompanying source code to my Bachelor's thesis at TUHH

Bayesian Non-Parametric Image Segmentation using HDP-MRF

Finding Areas Using the Monte Carlo Method

A basic PyTorch implementation of the Collaborative Sampling in Generative Adversarial Networks

Fun simulations and numerical calculations for the everyday physicist.

Real-time brain states tracking system and corticothalamic neural field parameter estimation

This repo contains code to perform Bootstrap Confidence Intervals estimation (a.k.a. Monte Carlo Confidence Interval or Empirical Confidence Interval estimation) for Machine Learing models.

Monte Carlo overview and their applications