Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
-
Updated
May 6, 2024 - Jupyter Notebook
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
PDE discovery using UBIC (uncertainty-penalized Bayesian information criterion)
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
Uncertainty-penalized Bayesian information criterion (UBIC) for PDE Discovery
A Python package implementing informational complexity (ICOMP) criteria for regression models
Accucopy is a computational method that infers Allele-Specific Copy Number alterations from low-coverage low-purity tumor sequencing data.
PyMC source program to determine the number of clusters in multi-dimensional data by WBIC.
University Project: using linear regression models to predict secondary market car prices based on a series of features. We will apply variable selection techniques and optimisation in attempt to build the best predictive model.
The project involves the analysis and forecasting of time series on financial data.
Unsupervised Extreme Learning Machine(ELM) is a non-iterative algorithm used for feature extraction. This method is applied on the IRIS Dataset for non-linear feature extraction and clustering using k-means, Self Organizing Maps(Kohonen Network) and EM Algorithm
Sign Language Recognizer
Term 1 Project 3 Design a Sign Language Recognition System by Luke Schoen for Udacity Artificial Intelligence Nanodegree (AIND)
Add a description, image, and links to the bayesian-information-criterion topic page so that developers can more easily learn about it.
To associate your repository with the bayesian-information-criterion topic, visit your repo's landing page and select "manage topics."