13 citations · 34 across the 11 of their papers we have counts for
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cs.LG2021
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias
Frederic Koehler, Viraj Mehta, Chenghui Zhou +1
Variational Autoencoders are one of the most commonly used generative models, particularly for image data. A prominent difficulty in training VAEs is data that is supported on a lo…
cs.LG2021★ 4 cited
An Experimental Design Perspective on Model-Based Reinforcement Learning
Viraj Mehta, Biswajit Paria, Jeff Schneider +2
In many practical applications of RL, it is expensive to observe state transitions from the environment. For example, in the problem of plasma control for nuclear fusion, computing…