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Found 4 papers, 1 papers with code
Minimizing $f$-Divergences by Interpolating Velocity Fields
To perform such movements we need to calculate the corresponding velocity fields which include a density ratio function between these two distributions.
Robust Neural Posterior Estimation and Statistical Model Criticism
In this work we revisit neural posterior estimation (NPE), a class of algorithms that enable black-box parameter inference in simulation models, and consider the implication of a simulation-to-reality gap.
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
We introduce Sequential Neural Posterior Score Estimation (SNPSE) and Sequential Neural Likelihood Score Estimation (SNLSE), two new score-based methods for Bayesian inference in simulator-based models.
Variational Likelihood-Free Gradient Descent
In many scientific applications, we do not have explicit access to the likelihood function.
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