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Tensor Monte Carlo: particle methods for the GPU era
[article]
2019
arXiv
pre-print
Multi-sample, importance-weighted variational autoencoders (IWAE) give tighter bounds and more accurate uncertainty estimates than variational autoencoders (VAE) trained with a standard single-sample objective. However, IWAEs scale poorly: as the latent dimensionality grows, they require exponentially many samples to retain the benefits of importance weighting. While sequential Monte-Carlo (SMC) can address this problem, it is prohibitively slow because the resampling step imposes sequential
arXiv:1806.08593v3
fatcat:rtlm6ux6yfgxvhnjow4gulai3q