14 citations · 38 across the 9 of their papers we have counts for
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cs.LG2019
Learning Correlated Latent Representations with Adaptive Priors
Da Tang, Dawen Liang, Nicholas Ruozzi +1
Variational Auto-Encoders (VAEs) have been widely applied for learning compact, low-dimensional latent representations of high-dimensional data. When the correlation structure amon…
cs.LG2019★ 9 cited
Correlated Variational Auto-Encoders
Da Tang, Dawen Liang, Tony Jebara +1
Variational Auto-Encoders (VAEs) are capable of learning latent representations for high dimensional data. However, due to the i.i.d. assumption, VAEs only optimize the singleton v…
cs.LG2019★ 3 cited
The Variational Predictive Natural Gradient
Da Tang, Rajesh Ranganath
Variational inference transforms posterior inference into parametric optimization thereby enabling the use of latent variable models where otherwise impractical. However, variation…