Simulation-based inference toolkit
-
Updated
Jul 3, 2024 - Python
Simulation-based inference toolkit
Community-sourced list of papers and resources on neural simulation-based inference.
Julia package for neural estimation
distributed, likelihood-free inference
Cosmology from HI maps using CNNs in PyTorch
Roundtrip: density estimation with deep generative neural networks
A system for scientific simulation-based inference at scale.
Normalizing flow models allowing for a conditioning context, implemented using Jax, Flax, and Distrax.
Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference
Likelihood-free AMortized Posterior Estimation with PyTorch
Code for "Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods" (arxiv:2305.04634)
This is an interactive app (run on local computer) to visualize neural likelihood surfaces from the paper "Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods"
Detection is truncation: studying source populations with truncated marginal neural ratio estimation. Code repository associated with https://arxiv.org/abs/2211.04291.
Comparison of summary statistic selection methods with a unifying perspective.
PyTorch implementation of inference aware neural optimisation (de Castro and Dorigo, 2018 https://www.sciencedirect.com/science/article/pii/S0010465519301948)
Mining gold from implicit models to improve likelihood-free inference, example for ROLR and RASCAL.
Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation
Simulator of the Lotka-Volterra prey-predator system with demographic and observational noise and biases
Probing the nature of dark matter by inferring the dark matter particle mass with machine learning and stellar streams.
Add a description, image, and links to the likelihood-free-inference topic page so that developers can more easily learn about it.
To associate your repository with the likelihood-free-inference topic, visit your repo's landing page and select "manage topics."