23 citations · 109 across the 19 of their papers we have counts for
Showing 2020Show all
3 papers · 1 filter
cs.LG2020
Learning Disentangled Latent Factors from Paired Data in Cross-Modal Retrieval: An Implicit Identifiable VAE Approach
Minyoung Kim, Ricardo Guerrero, Vladimir Pavlovic
We deal with the problem of learning the underlying disentangled latent factors that are shared between the paired bi-modal data in cross-modal retrieval. Our assumption is that th…
cs.LG2020★ 6 cited
Recursive Inference for Variational Autoencoders
Minyoung Kim, Vladimir Pavlovic
Inference networks of traditional Variational Autoencoders (VAEs) are typically amortized, resulting in relatively inaccurate posterior approximation compared to instance-wise vari…
cs.LG2020
Ordinal-Content VAE: Isolating Ordinal-Valued Content Factors in Deep Latent Variable Models
Minyoung Kim, Vladimir Pavlovic
In deep representational learning, it is often desired to isolate a particular factor (termed {\em content}) from other factors (referred to as {\em style}). What constitutes the c…