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