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stat.ML2020★ 3 cited
Composing Normalizing Flows for Inverse Problems
Jay Whang, Erik M. Lindgren, Alexandros G. Dimakis
Given an inverse problem with a normalizing flow prior, we wish to estimate the distribution of the underlying signal conditioned on the observations. We approach this problem as a…
stat.ML2019★ 2 cited
Training Variational Autoencoders with Buffered Stochastic Variational Inference
Rui Shu, Hung H. Bui, Jay Whang +1
The recognition network in deep latent variable models such as variational autoencoders (VAEs) relies on amortized inference for efficient posterior approximation that can scale up…