View source for Evidence Lower Bound

The '''evidence lower bound''' (ELBO) is the negative of the [[Variational Free Energy|variational free energy]], and the standard optimization objective in variational Bayesian inference. Maximizing the ELBO tightens the lower bound on the log-evidence of a generative model, bringing the approximate posterior closer to the true posterior. The ELBO decomposes into a reconstruction term — how well the model explains the data — and a regularization term — how much the approximate posterior diverges from the [[Prior Distribution|prior distribution]]. This decomposition reveals that every inference system faces a trade-off between fitting the data and respecting prior structure. In the [[Free Energy Principle]], the ELBO is the quantity that biological systems are implicitly maximizing when they learn from experience.

[[Category:Systems]]
[[Category:Mathematics]]