4 citations · 8 across the 3 of their papers we have counts for
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cs.LG2022★ 1 cited
Semi-Autoregressive Energy Flows: Exploring Likelihood-Free Training of Normalizing Flows
Phillip Si, Zeyi Chen, Subham Sekhar Sahoo +2
Training normalizing flow generative models can be challenging due to the need to calculate computationally expensive determinants of Jacobians. This paper studies the likelihood-f…
cs.LG2021★ 4 cited
Autoregressive Quantile Flows for Predictive Uncertainty Estimation
Phillip Si, Allan Bishop, Volodymyr Kuleshov
Numerous applications of machine learning involve representing probability distributions over high-dimensional data. We propose autoregressive quantile flows, a flexible class of n…