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Research map / Probabilistic and scientific modeling / Variational and generative sampling

A Spectral Approach to Gradient Estimation for Implicit Distributions

ICML 2018 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Annealing and divergence-based variational objectives · 43 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use SSGE instead of Stein+ for gradient estimatesGradient-free HMC · UCI Glass hyperparameter posterioraverage acceptance ratioHelped
Use SSGE instead of KMC for gradient-free HMCGradient-free HMC · UCI Glass hyperparameter posterioraverage acceptance ratioHelped
Use SSGE for out-of-sample gradient estimationGradient estimation for a standard Gaussian · 1-D standard Gaussiangradient estimation accuracyHelped
Add the entropy term, estimated using SSGE (ablation)Implicit VAE · CelebAsample qualityHelped
Add SSGE-estimated entropy gradients to the Implicit VAEImplicit VAE · CelebAFIDHelped
Use SSGE with an implicit posterior instead of a factorized Gaussian posteriorBayesian neural network · 1-D regressionpredictive uncertaintyMixed
Use SSGE with a factorized posterior instead of BBBBayesian neural network · 1-D regressionpredictionNo clear effect

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