sbi-dev/sbi

Simulation-based inference toolkit

Language: Python - Size: 72.6 MB - Last synced: 1 day ago - Pushed: 1 day ago - Stars: 525 - Forks: 126

ICB-DCM/pyABC

distributed, likelihood-free inference

Language: Python - Size: 46.4 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 195 - Forks: 42

kimmo1019/Roundtrip

Roundtrip: density estimation with deep generative neural networks

Language: Python - Size: 2.26 MB - Last synced: 18 days ago - Pushed: 18 days ago - Stars: 62 - Forks: 13

undark-lab/swyft

A system for scientific simulation-based inference at scale.

Language: Jupyter Notebook - Size: 380 MB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 151 - Forks: 13

probabilists/lampe

Likelihood-free AMortized Posterior Estimation with PyTorch

Language: Python - Size: 3.68 MB - Last synced: 22 days ago - Pushed: 3 months ago - Stars: 105 - Forks: 8

pablodecm/paper-inferno

Code and manuscript for the paper "INFERNO: Inference-Aware Neural Optimisation". Automated mirror from CERN GitLab.

Language: Python - Size: 1.51 MB - Last synced: 21 days ago - Pushed: almost 4 years ago - Stars: 4 - Forks: 4

florent-leclercq/Bayes_InfoTheory

Lectures on Bayesian statistics and information theory

Language: Jupyter Notebook - Size: 29.3 MB - Last synced: 10 months ago - Pushed: over 2 years ago - Stars: 28 - Forks: 3

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.

Language: Jupyter Notebook - Size: 12.8 MB - Last synced: 9 months ago - Pushed: over 1 year ago - Stars: 15 - Forks: 3

smsharma/jax-conditional-flows

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

Language: Jupyter Notebook - Size: 1.31 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 7 - Forks: 3

smsharma/awesome-neural-sbi

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

Size: 51.8 KB - Last synced: 2 days ago - Pushed: 2 months ago - Stars: 63 - Forks: 3

montefiore-ai/balanced-nre

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

Language: Jupyter Notebook - Size: 2.98 MB - Last synced: 12 months ago - Pushed: over 1 year ago - Stars: 11 - Forks: 2

mjvakili/ccppabc

Approximate Bayesian Computation

Language: Jupyter Notebook - Size: 52.8 MB - Last synced: 29 days ago - Pushed: about 7 years ago - Stars: 1 - Forks: 1

florent-leclercq/pyselfi

Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation

Language: Jupyter Notebook - Size: 44.7 MB - Last synced: 2 months ago - Pushed: over 1 year ago - Stars: 10 - Forks: 1

GilesStrong/pytorch_inferno

PyTorch implementation of inference aware neural optimisation (de Castro and Dorigo, 2018 https://www.sciencedirect.com/science/article/pii/S0010465519301948)

Language: Jupyter Notebook - Size: 30.8 MB - Last synced: 11 days ago - Pushed: about 1 year ago - Stars: 4 - Forks: 1

jmwalchessen/neural_likelihood

Code for "Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods" (arxiv:2305.04634)

Language: Jupyter Notebook - Size: 41.1 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 1 - Forks: 1

florent-leclercq/correlations_vs_field

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

Language: Jupyter Notebook - Size: 130 MB - Last synced: 4 months ago - Pushed: over 1 year ago - Stars: 4 - Forks: 0

nicolossus/pylfi

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

Language: Python - Size: 9.31 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 1 - Forks: 0

lucien1011/abc-ml-inference

My framework to perform likelihood-free inference with toy models or real-life simulation

Language: Python - Size: 34.2 KB - Last synced: 2 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

andrejobuljen/CNN-HI

Cosmology from HI maps using CNNs

Language: Jupyter Notebook - Size: 11.1 MB - Last synced: 5 days ago - Pushed: 7 days ago - Stars: 0 - Forks: 0

msainsburydale/NeuralEstimators.jl

Julia package for neural estimation

Language: Julia - Size: 2.52 MB - Last synced: 1 day ago - Pushed: 1 day ago - Stars: 11 - Forks: 0

francois-rozet/amnre 📦

Arbitrary Marginal Neural Ratio Estimation for Likelihood-free Inference

Language: Python - Size: 3.84 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 2 - Forks: 0

tillahoffmann/summaries

Comparison of summary statistic selection methods with a unifying perspective.

Language: Python - Size: 229 KB - Last synced: about 2 months ago - Pushed: 11 months ago - Stars: 0 - Forks: 0

tillahoffmann/summaries2

Language: Python - Size: 171 KB - Last synced: about 2 months ago - Pushed: 8 months ago - Stars: 0 - Forks: 0

jmwalchessen/neural_likelihood_interactive_app

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"

Language: Python - Size: 679 KB - Last synced: 8 months ago - Pushed: 8 months ago - Stars: 0 - Forks: 0

tillahoffmann/coaloracle

Repository for simulated genetic data presented by Nunes and Balding (2010).

Language: Makefile - Size: 9.77 KB - Last synced: about 2 months ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0

ocbe-uio/elfi Fork of elfi-dev/elfi

A Python package for likelihood-free inference (LFI) methods such as Approximate Bayesian Computation (ABC)

Language: Python - Size: 1.27 MB - Last synced: about 1 year ago - Pushed: about 3 years ago - Stars: 2 - Forks: 0

JBris/model-calibration-evaluation

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

Language: Python - Size: 3.92 MB - Last synced: 3 months ago - Pushed: 3 months ago - Stars: 5 - Forks: 0

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

Language: Julia - Size: 96.7 KB - Last synced: 4 months ago - Pushed: almost 2 years ago - Stars: 1 - Forks: 0

JuliaApproxInference/LikelihoodfreeInference.jl

Likelihood-Free Inference for Julia.

Language: Julia - Size: 11.2 MB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 5 - Forks: 0

leonrenn/MINING-GOLD-FROM-GENERATORS

Mining gold from implicit models to improve likelihood-free inference, example for ROLR and RASCAL.

Language: Jupyter Notebook - Size: 446 KB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0

ocbe-uio/PriorElicitation

Shiny application for prior elicitation experiments from "Probabilistic elicitation of expert knowledge through assessment of computer simulations"

Language: R - Size: 285 KB - Last synced: 9 months ago - Pushed: over 2 years ago - Stars: 1 - Forks: 0

gutmanngroup/bedimplicit Fork of stevenkleinegesse/bedimplicit

Source code for "Efficient Bayesian Experimental Design for Implicit Models", AISTATS 2019, https://arxiv.org/abs/1810.09912

Size: 1.21 MB - Last synced: 8 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0

gutmanngroup/minebed Fork of stevenkleinegesse/minebed

Source code for Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation, ICML 2020, https://arxiv.org/abs/2002.08129

Size: 2.44 MB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 0

gutmanngroup/idad Fork of desi-ivanova/idad

Python code for "Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods", NeurIPS, 2021, https://proceedings.neurips.cc/paper/2021/hash/d811406316b669ad3d370d78b51b1d2e-Abstract.html

Size: 72.3 KB - Last synced: 8 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0

gutmanngroup/GradBED Fork of stevenkleinegesse/GradBED

Code for the paper "Gradient-Based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds" https://arxiv.org/abs/2105.04379

Size: 1.47 MB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 0 - Forks: 0

florent-leclercq/lotkavolterra_simulator

Simulator of the Lotka-Volterra prey-predator system with demographic and observational noise and biases

Language: Jupyter Notebook - Size: 861 KB - Last synced: 15 days ago - Pushed: over 1 year ago - Stars: 2 - Forks: 0