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Found 4 papers, 3 papers with code
Model Comparison in Approximate Bayesian Computation
In particular, I train a mixture-density network to map features of the observed data to the posterior probability of the models.
GATSBI: Generative Adversarial Training for Simulation-Based Inference
We study the relationship between SBI and GANs, and introduce GATSBI, an adversarial approach to SBI.
Benchmarking Simulation-Based Inference
We set out to fill this gap: We provide a benchmark with inference tasks and suitable performance metrics, with an initial selection of algorithms including recent approaches employing neural networks and classical Approximate Bayesian Computation methods.
SBI -- A toolkit for simulation-based inference
$\texttt{sbi}$ facilitates inference on black-box simulators for practising scientists and engineers by providing a unified interface to state-of-the-art algorithms together with documentation and tutorials.
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