Compressing RGB images using SVD matrix decomposition
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Updated
Sep 2, 2021 - Jupyter Notebook
Compressing RGB images using SVD matrix decomposition
Fatoração de Matrizes para Sistemas de Classificação de Machine Learning
The code for prototype selection and instance ranking using matrix decomposition and subspace learning
Fondements de l’Algorithmique Algébrique. Implémentation de différent algorithme appliqué à des matrices à coefficients dans Z/nZ.
It is one of my three seminars for Master degree in TU Chemnitz
This package contains implementations of efficient representations and updating algorithms for Cholesky factorizations.
Example of an estimation of cell-type proportions using reference-free method (RefFreeEWAS)
A on-going crate that provides basic matrix manipulations and ports and python's scipy-sklearn's matrix decomposition to pure Rust
Implementation of the Finite Element Method (FEM) to solve static equilibrium problems using rectangular elements (2D)
This class solves the problem of decomposition of an arbitrary matrix into a series of primitive matrices, which are rotations, scaling and translation. Solves the problem of the lack of mechanisms for working with the skew-component of the matrix, for example, in Unity.
implement machine learning models from scratch
A recommendation engine based on user behavior and social network data, to surface content most likely to be relevant to a user on IBM Watson Studio Platform. Used collaborative filtering & matrix factorization techniques.
This repository contains Python functions implementing the Hoffman algorithm for decomposing elements of SO(N), and functions applying this algorithm to decompose any element of the matchgate group into nearest-neighbor matchgates. See README for more information and a list of references on the Hoffman decomposition and the matchgate group.
Cholesky decomposition for Hilbert matrix of any order in Python 3 (Two programs)
This package contains a data structure that wraps a matrix of matrices or factorizations and acts like the matrix resulting from concatenating the input matrices without allocating further memory.
Analysis repository for Taniguchi et al. 2021, AJ, 162, 111
Models to detect real pictures from fake photoshoped pictures
Reformulation of SDPs using block factor-width two matrices
Numerical Techniques (Matrix Decomposition, Matrix Equation Solvers, Inversion, Iterative Root Finding), All Implemented from scratch in Python
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