Ecosyste.ms: Repos
An open API service providing repository metadata for many open source software ecosystems.
GitHub topics: likelihood-free-inference
msainsburydale/NeuralEstimators.jl
Julia package for neural estimation
Language: Julia - Size: 2.4 MB - Last synced: about 1 hour ago - Pushed: about 7 hours ago - Stars: 11 - Forks: 0
sbi-dev/sbi
Simulation-based inference toolkit
Language: Python - Size: 74.6 MB - Last synced: about 1 hour ago - Pushed: about 2 hours ago - Stars: 521 - Forks: 126
kimmo1019/Roundtrip
Roundtrip: density estimation with deep generative neural networks
Language: Python - Size: 2.26 MB - Last synced: 2 days ago - Pushed: 2 days ago - Stars: 62 - Forks: 13
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: 5 days ago - Pushed: almost 4 years ago - Stars: 4 - Forks: 4
probabilists/lampe
Likelihood-free AMortized Posterior Estimation with PyTorch
Language: Python - Size: 3.68 MB - Last synced: 6 days ago - Pushed: 3 months ago - Stars: 105 - Forks: 8
smsharma/awesome-neural-sbi
Community-sourced list of papers and resources on neural simulation-based inference.
Size: 51.8 KB - Last synced: 1 day ago - Pushed: about 2 months ago - Stars: 60 - Forks: 3
mjvakili/ccppabc
Approximate Bayesian Computation
Language: Jupyter Notebook - Size: 52.8 MB - Last synced: 13 days ago - Pushed: about 7 years ago - Stars: 1 - Forks: 1
ICB-DCM/pyABC
distributed, likelihood-free inference
Language: Python - Size: 46.4 MB - Last synced: 18 days ago - Pushed: 18 days ago - Stars: 195 - Forks: 42
undark-lab/swyft
A system for scientific simulation-based inference at scale.
Language: Jupyter Notebook - Size: 380 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 151 - Forks: 13
tillahoffmann/summaries2
Language: Python - Size: 171 KB - Last synced: about 1 month ago - Pushed: 7 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 1 month ago - Pushed: almost 2 years ago - Stars: 0 - 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: about 2 months ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0
florent-leclercq/pyselfi
Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation
Language: Jupyter Notebook - Size: 44.7 MB - Last synced: about 2 months ago - Pushed: over 1 year ago - Stars: 10 - Forks: 1
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: about 1 month ago - Pushed: over 1 year 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
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: about 2 months ago - Pushed: about 2 months ago - Stars: 7 - Forks: 3
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: almost 3 years ago - Stars: 0 - 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
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
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
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: 8 months ago - Pushed: over 1 year ago - Stars: 15 - Forks: 3
florent-leclercq/Bayes_InfoTheory
Lectures on Bayesian statistics and information theory
Language: Jupyter Notebook - Size: 29.3 MB - Last synced: 9 months ago - Pushed: over 2 years ago - Stars: 28 - Forks: 3
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
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
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
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
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
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: 12 months ago - Pushed: about 3 years ago - Stars: 2 - 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: 3 months ago - Pushed: over 1 year ago - Stars: 1 - Forks: 0
tillahoffmann/summaries
Comparison of summary statistic selection methods with a unifying perspective.
Language: Python - Size: 229 KB - Last synced: about 1 month ago - Pushed: 10 months ago - Stars: 0 - Forks: 0
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: 5 days ago - Pushed: about 1 year ago - Stars: 4 - Forks: 1
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
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: 3 months ago - Pushed: over 1 year ago - Stars: 4 - Forks: 0