daubl: Digit analysis using Benford's law
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Updated
Sep 22, 2020 - R
daubl: Digit analysis using Benford's law
Compatibility probability of measurements across experiments
Code relative to paper arXiv:1808.01930 [hep-ex]
Bayesian Inference
A curated list of my Artificial Intelligence project.
Markov Chain Monte Carlo on graph space applied to the study of neuronal interactions from experimental data
AbstractGPs.jl is a package that defines a low-level API for working with Gaussian processes (GPs), and basic functionality for working with them in the simplest cases. As such it is aimed more at developers and researchers who are interested in using it as a building block than end-users of GPs.
Bayesian Logistic Regression with Python and PyMC3 to predict customer subscription for a financial institution.
Tools for the Bayesian Discount Prior Function
Implementation of Markov chain Monte Carlo sampling and the Metropolis-Hastings algorithm for multi-parameter Bayesian inference.
Kronecker-product-based linear inversion under Gaussian and separability assumptions.
Histogram based classification and prediction of annual rainfall from Kerala dataset
pcal: Calibration of p-values for point null hypotheses
Matrix Determinant Toolkit
The Plausible Parameter Space (PPS) Shiny App is designed to help users define their priors in a linear regression with two regression coefficients.
Kronecker-product-based linear inversion under Gaussian and separability assumptions.
Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.
A web app for analyzing A/B testing data using Bayesian approach
R Package With Shiny App to Perform and Visualize Clustering of Count Data via Mixtures of Multivariate Poisson-log Normal Model
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
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