BayesDensity.jl: Bayesian nonparametric density estimation in Julia
Year: 2026
Type: software-paper
Abstract: BayesDensity.jl is a Julia package for Bayesian nonparametric estimation of smooth univariate densities. The package provides a unified interface to a range of well-established models from the statistical literature, supporting both Markov chain Monte Carlo and variational inference for most implemented procedures. Tailor-made inference algorithms facilitate computational efficiency across all supported models. The practical usage of the package is illustrated through several real-data examples, demonstrating its ability to produce smooth, interpretable density estimates with principled uncertainty quantification. The excellent computational performance of the package is demonstrated in two benchmarks.
Source: SoftwareX
Author: Oskar Høgberg Simensen
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W7166539293