127 citations · 278 across the 14 of their papers we have counts for
3 papers · 1 filter
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting
Aditya Grover, Jiaming Song, Alekh Agarwal +4
A learned generative model often produces biased statistics relative to the underlying data distribution. A standard technique to correct this bias is importance sampling, where sa…
The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models
Shengjia Zhao, Jiaming Song, Stefano Ermon
A large number of objectives have been proposed to train latent variable generative models. We show that many of them are Lagrangian dual functions of the same primal optimization…
Factored Temporal Sigmoid Belief Networks for Sequence Learning
Jiaming Song, Zhe Gan, Lawrence Carin
Deep conditional generative models are developed to simultaneously learn the temporal dependencies of multiple sequences. The model is designed by introducing a three-way weight te…