Monte Carlo simulation of 2D Ising Model. Final project of the LoCP-A course during 2020/2021 at Unipd

Image denoising using Markov random fields.

Neural Network Quantum State

Python code that performs that Feynman path integral for a specified potential. Demonstrated by approximating the average energy of the quantum harmonic oscillator for various temperatures.

metropolis-hastings random walk with PySpark

Bayesian maximum likelihood of a Black Sholes stochastic scenario generator.

Python code that simulates the 2D Ising Model on a square periodic lattice of arbitrary size using Markov Chain Monte Carlo.

MCMC parameter space sampling via Metropolis-Hastings

In the first semester of my MSc. studies, we developed a phyton version of the Gibbs Sampler and Metropolis-Hastings Algorithm from the scratch. We described our results and analysis in a report.

Companion Jupyter Notebook for "Self-Assembly of a Dimer System"

Performing a Sobol global sensitivity analysis on a flood risk model in Selinsgrove, PA

Topological Data Analysis for Parameter Estimation of Noisy Biexponential Decay (UD GEMS research project)

"AdamMCMC: Combining Metropolis Adjusted Langevin with Momentum-based Optimization"

Notebooks for Bayesian Foundations (Course 1)

Personal project, autumn 2019.

Markov Chain Monte Carlo algorithms.

Gerador de valores de uma distribuição de probabilidade bidimensional. Via algoritmo de Metropolis-Hastings.

Contains various machine learning algorithms and their implementations.

This assignment aims to develop a Gibbs sampling and Metropolis Hastings Algorithm to sample from a specified probability distribution.