There are 0 repository under multivariate-distributions topic.
Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainty that is often present in real-world datasets.
Additional univariate and multivariate distributions
Several examples of multivariate techniques implemented in R, Python, and SAS. Multivariate concrete dataset retrieved from https://archive.ics.uci.edu/ml/datasets/Concrete+Slump+Test. Credit to Professor I-Cheng Yeh.
An object-oriented approach to implement anomaly detection in Python using semi-supervised learning
Multivariate independent comparison of observations
Multivariate independent comparison of observations.
Collection of missing multivariate random number distributions for Modern C++ with STL-like API.
Random data generator from scratch. (Using numpy for simple mathematical functions only)
Implementation of the Extreme Joint Distribution algorithm in C++
Programa Computarizado, elaborado en el lenguaje de programacion MATLAB, referente al Trabajo Especial de Grado para optar al Título de Ingeniero Industrial, en la Facultad de Ingeniería de la Universidad de Carabobo, año 2015; la cual fue reconocida con mención honorífica.
Simulation of Partition-of-Unity copulas in R, e.g. for the purpose of modeling risk or for the creation of synthetic data based on restricted datasets
Here all my machine learning notebooks will be uploaded
UniBG modelli stocastici prova 00 a.a. 2017-2018
Implemented from scratch a sampling method to draw samples from a multivariate Normal (MVN) distribution in JAX.
A simple utility to perform sampling from multivariate distributions (supported by a PyTorch backend)
Provides multivariate normal distribution sampling and matrix inversion for Jetbrain's new NDArray library Multik, by bodging it with some classes (including tests) from Apache Commons Maths 3 & 4, translated into Kotlin and made JVM independent for a Kotlin Multi-Platform project.
Machine Learning algorithms using Sklearn and Scikit python libraries for comparing their behaviour on anomaly detection