
An analytical solution is proposed for approximating the gradient of the Evidence Lower Bound (ELBO) in variational inference problems where the statistical model is a Bayesian network consisting of observations drawn from a mixture of a Gaussian distribution embedded in unrelated clutter, known as the clutter problem.


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analytical-approximation-of-the-elbo-gradient-for-efficient-variational-inference-in-the-clutter-problem


Analytical Approximation of the ELBO Gradient for Efficient Variational Inference in the Clutter Problem
