#
multivariate-distributions
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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.
Updated
Apr 15, 2023
Jupyter Notebook
Additional univariate and multivariate distributions
Updated
Oct 4, 2023
Python
Copula fitting in Python.
Updated
Dec 4, 2023
Python
An object-oriented approach to implement anomaly detection in Python using semi-supervised learning
Updated
Jun 9, 2018
Jupyter Notebook
Multivariate independent comparison of observations
Updated
Jul 30, 2018
MATLAB
Updated
Oct 26, 2020
HTML
Robust estimation using heavy-tailed distributions
A Python Package to Create Synthetic Tabular Data
Updated
Apr 8, 2023
Jupyter Notebook
Multivariate independent comparison of observations.
Random data generator from scratch. (Using numpy for simple mathematical functions only)
Updated
Mar 16, 2018
Python
Collection of missing multivariate random number distributions for Modern C++ with STL-like API.
Updated
Jan 31, 2017
HTML
Implemented from scratch a sampling method to draw samples from a multivariate Normal (MVN) distribution in JAX.
Updated
Oct 28, 2022
Jupyter Notebook
A simple utility to perform sampling from multivariate distributions (supported by a PyTorch backend)
Updated
Jun 1, 2019
Python
Updated
Sep 6, 2022
Jupyter Notebook
Updated
Jul 26, 2024
MATLAB
Machine Learning algorithms using Sklearn and Scikit python libraries for comparing their behaviour on anomaly detection
Updated
Jun 28, 2018
Jupyter Notebook
A Collection of Basic Utilities for Statistical Analyses
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