Lectures on Bayesian statistics and information theory
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Updated
Sep 16, 2021 - Jupyter Notebook
Lectures on Bayesian statistics and information theory
Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation
Simulation-based inference in JAX
pyABC: distributed, likelihood-free inference
Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
A toolbox for C++ devs wanting to build geospatial population genetics simulators !
Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.
Evaluating model calibration methods for sensitivity analysis, uncertainty analysis, optimisation, and Bayesian inference
Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation
ABC random forests for model choice and parameter estimation, pure C++ implementation
Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening
CE-ABC is a code to simulate the epidemic outbreaks with mechanistic models through a cross-entropy approximate Bayesian framework.
The official code repo for HyperAgent algorithm published in ICML 2024.
Likelihood-Free Inference for Julia.
User interface to DIYABC/AbcRanger
Trabajo de Fin de Grado de Física 2022
Correlation functions versus field-level inference in cosmology: example with log-normal fields
A simulation model for the digital reconstruction of 3D root system architectures. Integrated with a simulation-based inference generative deep learning model.
Figuring out how Approximate Bayesian Computation works and how it can be applied to geological modeling.
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