Introdução a regressão e modelos lineares
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Updated
Mar 8, 2023 - TeX
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Introdução a regressão e modelos lineares
A tex configuration file for inserting formatted code, including Julia language.
Solving Cauchy problems and stiff systems of differential equations, finding eigenvalues in symmetric matrices
This repo implements the Metropolis–Hastings algorithm (MCMC method) and the Swendsen–Wang cluster algorithm for the Ising model
This code implements the Jackknife resampling algorithm.
Team project for the 2019 COMAP Mathematical Contest in Modeling (MCM).
A repository with some thoughts about the Fibonacci sequence
Solving integral equations of the first kind, parabolic and elliptical partial differential equations
Thesis for the Computational Science Master's program at Central Washington University. 3D extension of an analog of cosmological particle creation in a Friedmann-Robertson-Walker universe by numerically simulating a Bose-Einstein condensate with a time-dependent scattering length.
A simple molecular dynamics demo using Julia
Presentations on some of the computer methods considered in the course
Materials developed during the laboratory work at the astrophysical workshop
Plotting tools for teaching and learning complex analysis
A julia library to create randomly generated Mathematics questions.
Literate programming approach for LAR in Julia, source of https://github.com/cvdlab/LARLIB.jl
Geometric Constraints in Algorithmic Design — M.Sc. Thesis in Computer Science and Engineering
Replication of Glass and Sun (1994) submitted to ReScience C
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012