24 citations · 35 across the 10 of their papers we have counts for
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cs.LG2020
Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Normalizing flows are among the most popular paradigms in generative modeling, especially for images, primarily because we can efficiently evaluate the likelihood of a data point.…
cs.LG2020
From Boltzmann Machines to Neural Networks and Back Again
Surbhi Goel, Adam Klivans, Frederic Koehler
Graphical models are powerful tools for modeling high-dimensional data, but learning graphical models in the presence of latent variables is well-known to be difficult. In this wor…