Latent Variable Sampling

Data augmentation using Polya-Gamma latent variables.

Introduced by Polson et al. in Bayesian inference for logistic models using Polya-Gamma latent variables

This method applies Polya-Gamma latent variables as a way to obtain closed form expressions for full-conditionals of posterior distributions in sampling algorithms like MCMC.

Source: Bayesian inference for logistic models using Polya-Gamma latent variables

Papers


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Tasks


Task Papers Share
General Classification 2 28.57%
Few-Shot Learning 1 14.29%
Incremental Learning 1 14.29%
Point Processes 1 14.29%
Multi-Armed Bandits 1 14.29%
Numerical Integration 1 14.29%

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🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

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