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Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space

ICML 2023 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Variational inference theory and gradients · 1 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use the entropy JKO proximal step in place of the prior strongly log-concave approachStochastic FB-GVI · Strongly log-concave targetiteration complexity: Õ(β²d/(α²ε²)) -> Õ(βd/(αε²))Helped
Use FB-GVI rather than BWGDGaussian VI · Gaussian targetsmaximum stable step sizeHelped
Use (stochastic) FB-GVI rather than BWGDGaussian VI · Gaussian targets and Bayesian logistic regressionobjective valueMixed

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