JOSS Papers: bayesian-methods

Published Papers

published Published 4 months ago

IntrinsicTimescales.jl: A Julia package to estimate intrinsic (neural) timescales (INTs) from time-series data

Julia

10.21105/joss.08261

published Published almost 2 years ago

GrainLearning: A Bayesian uncertainty quantification toolbox for discrete and continuum numerical models of granular materials

Python PureBasic Jupyter Notebook

10.21105/joss.06338

published Published almost 2 years ago

DAPPER: Data Assimilation with Python: a Package for Experimental Research

Python Fortran

10.21105/joss.05150

published Published about 6 years ago

Geometric nested sampling: sampling from distributions defined on non-trivial geometries

Python

10.21105/joss.01809

published Published over 6 years ago

BayesPostEst: An R Package to Generate Postestimation Quantities for Bayesian MCMC Estimation

R

10.21105/joss.01722

published Published over 7 years ago

hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems

Python C++ Jupyter Notebook

10.21105/joss.00940

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ISSN 2475-9066