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
pyABC: distributed, likelihood-free inference
Simulation-based inference in JAX
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 !
Simulator Expansion for Likelihood-Free Inference (SELFI): a python implementation
ABC random forests for model choice and parameter estimation, pure C++ implementation
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
Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening
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
Figuring out how Approximate Bayesian Computation works and how it can be applied to geological modeling.
Simulator of the Lotka-Volterra prey-predator system with demographic and observational noise and biases
A Python package for likelihood-free inference (LFI) methods such as Approximate Bayesian Computation (ABC)
GPU and TPU implementation of parallelized ABC inference for a stochastic epidemiology model for COVID-19
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