msainsburydale/NeuralEstimators.jl
Julia package for simulation-based, likelihood-free parameter inference using neural networks.
This tool helps researchers and scientists quickly estimate parameters from complex simulations, even when traditional statistical methods are too slow or impossible. You input your simulated data and observations, and it efficiently provides estimates of your model's parameters. This is ideal for statisticians, data scientists, and researchers working with simulation-based models in fields like physics, biology, or economics.
Use this if you need to rapidly estimate parameters from many different observed datasets using complex simulation models where the likelihood function is difficult or impossible to calculate.
Not ideal if your statistical model has a simple, known likelihood function that can be easily computed with conventional methods.
Stars
33
Forks
2
Language
Julia
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/msainsburydale/NeuralEstimators.jl"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
CliMA/Oceananigans.jl
🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs
JuliaLang/julia
The Julia Programming Language
WassimTenachi/PhySO
Physical Symbolic Optimization
EnzymeAD/Enzyme.jl
Julia bindings for the Enzyme automatic differentiator
astroautomata/SymbolicRegression.jl
Distributed High-Performance Symbolic Regression in Julia