maximum-a-posteriori

Python package for automatically superimposing data sets to create a master curve, using Gaussian process regression and maximum a posteriori estimation.

Colored/White Guassian Noise Removal via Adaptive Thresholding in Curvelet Domain

Codes and data for the paper "Gaussian Process Regression and Conditional Karhunen-Loève Models for Data Assimilation in Inverse Problems"

Maximum Likelihood and MAP estimation for polynomial regression under Gaussian and Poisson noise, comparing Normal Equations, Gradient Descent, and SGD solvers.

B-FADE: Bayesian FAtigue moDel Estimator

A brief comparison of the weights computation for a linear classifer using Maximum Likelihood (ML) and Maximum aPosteriori (MAP)