simulation-based-inference

undark-lab/swyft

A system for scientific simulation-based inference at scale.

probabilists/lampe

Likelihood-free AMortized Posterior Estimation with PyTorch

smsharma/awesome-neural-sbi

Community-sourced list of papers and resources on neural simulation-based inference.

mackelab/delfi

Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead

montefiore-institute/hypothesis

A Python toolkit for (simulation-based) inference and the mechanization of science.

hyunjimoon/SBC

probcomp/Genify.jl

Automatically convert Julia methods to Gen functions.

wangbingjie/sbi_pp

Simulation-based (likelihood-free) inference customized for astronomical applications

mlcolab/sbi-workshop

SBI Workshop jointly by Helmholtz AI + ML ⇌ Science Colaboratory

ma921/SOBER

Fast Bayesian optimization, quadrature, inference over arbitrary domain with GPU parallel acceleration

JoeriHermans/constraining-dark-matter-with-stellar-streams-and-ml

Probing the nature of dark matter by inferring the dark matter particle mass with machine learning and stellar streams.

ma921/BASQ

(NeurIPS 2022) Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination

dirmeier/sbijax

Simulation-based inference in JAX

msainsburydale/NeuralEstimators.jl

Julia package for neural estimation

swagnercarena/paltas

Conduct simulation-based inference on strong gravitational lensing systems.

montefiore-institute/balanced-nre

Code for the paper "Towards Reliable Simulation-Based Inference with Balanced Neural Ratio Estimation".

PEREGRINE-GW/peregrine

A simulation-based Inference (SBI) library designed to perform analysis on a wide class of gravitational wave signals

smsharma/hierarchical-inference

Hierarchical neural implicit inference over event ensembles. Code repository associated with https://arxiv.org/abs/2306.12584.

JBris/model-calibration-evaluation

Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference

MaximeVandegar/NEB

Code for reproducing the experiments in the paper Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference.

smsharma/jax-conditional-flows

Normalizing flow models allowing for a conditioning context, implemented using Jax, Flax, and Distrax.

ThomasGesseyJones/FullyBayesianForecastsExample

Example of a fully Bayesian forecast using evidence networks applied to 21-cm cosmology

trivnguyen/JeansGNN

Neural Simulation-based Inference with GNN for Jeans Modeling

yandexdataschool/inverse-problem-intensive

A short course on simulation-based infernce for physics at YSDA in April 2021

florent-leclercq/correlations_vs_field

Correlation functions versus field-level inference in cosmology: example with log-normal fields

mackelab/sbi-for-connectomics

Research code and results for the paper "Simulation-based inference for computational connectomics" (Boelts et al. 2023 PLoS CB, @janfb)

Spinkoo/Simulink-based-inference

This repo contains examples of how to use Simulink simulation to perform simulation-based inference calculations in Python

dirmeier/ssnl

Simulation-based inference using SSNL

francois-rozet/amnre

Arbitrary Marginal Neural Ratio Estimation for Likelihood-free Inference

matteoruth/npe-astrometry-betapic

rbarrue/sally_cpv_wh

Created for benchmarking different techniques to search for CP violation in the HWW vertex in leptonic WH production.

SourabhKul/ABC-COVID-19-GPU-TPU

GPU and TPU implementation of parallelized ABC inference for a stochastic epidemiology model for COVID-19

VogelsLab/fSBI

Companion code to Confavreux*, Ramesh*, Goncalves, Macke* & Vogels*, Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference, NeurIPS 2023

JuliaEpi/MathepiaInference.jl

Bayesian inference tools. Including state-of-the-art inference methods: HMC family, ABC family, Data assimilation, and so on. Part of Mathepia.jl

nicolossus/pylfi

pyLFI is a Python toolbox using likelihood-free inference (LFI) methods for estimating the posterior distributions of model parameters.