Homeworks on "Computational Statistics" course
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Updated
May 6, 2022 - Jupyter Notebook
Homeworks on "Computational Statistics" course
Master Lab: Conditional Resampled Importance Sampling and ReSTIR
Implemented algorithms from a numerical stochastic methods university course
Integration with Monte Carlo method
Programs written using MPI and OpenMP
First one day project for the computational statistics module.
CUHK Course code: STAT 3011 | This course is designed to strengthen students' ability in statistical computing as well as in processing and analysing data. Students are required to participate in several term projects with emphasis on techniques of data management and analysis.
Monte Carlo integration is particularly useful when dealing with high-dimensional integrals or integrals over complex, irregularly shaped domains where traditional methods may be impractical. It's widely used in various fields, including physics, finance, and engineering, for solving problems involving numerical integration.
Pi Approximation written in C++17
Monte Carlo Ray Tracer implemented from scratch in C++. Made in the course TNCG15 Advanced Global Illumination and Rendering at Linköping University.
Computation of the noise intensity spectrum induced by turbulent boundary layer on the surface of subsonic passenger aircraft using eigen frequencies approach.
A new Python wrapper for the Cuba library
Criação de um algoritmo que calcula a média de consumo de memória usando interpolação por Splines e integração por Monte Carlo. Trabalho realizado no 3º de Ciência da Computação do Instituto Federal de Minas Gerais(IFMG) - Campus Formiga para a Disciplina Cálculo Numérico
Monte Carlo Method (MCM) for incorporating measurement uncertainty in the frequentist analysis of occupational exposure by inhalation to chemical agents
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