A simple but generic implementation of Expectation Maximization algorithms to fit mixture models.
MIT License
Julia implementation of elliptical slice sampling.
Approximate variational inference in Julia
A Julia package for robust regressions using M-estimators and quantile regressions
Non-homogenous Hidden Markov Models
Evidential Deep Learning Layers for Flux
Julia package for function approximation
A hybrid sampler for the Pólya-Gamma distribution in Julia, implementing multiple algorithms for ...
A unified interface for simulating and evaluating sequential sampling models in Julia.
Distributed MCMC Inference in Dirichlet Process Mixture Models (High Performance Machine Learning...
A Julia package that implements a category of reaction (transportation) network-type dynamical sy...
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
A Julia package for differentiating through expectations with Monte-Carlo estimates
Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesia...
Multi-language suite for high-performance solvers of differential equations and scientific machin...
Linear Regression for Julia