155 citations · 945 across the 25 of their papers we have counts for
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stat.ML2021★ 3 cited
Marginalizable Density Models
Dar Gilboa, Ari Pakman, Thibault Vatter
Probability density models based on deep networks have achieved remarkable success in modeling complex high-dimensional datasets. However, unlike kernel density estimators, modern…
stat.ML2018★ 3 cited
Amortized Bayesian inference for clustering models
Ari Pakman, Liam Paninski
We develop methods for efficient amortized approximate Bayesian inference over posterior distributions of probabilistic clustering models, such as Dirichlet process mixture models.…
stat.ML2016★ 9 cited
Partition Functions from Rao-Blackwellized Tempered Sampling
David Carlson, Patrick Stinson, Ari Pakman +1
Partition functions of probability distributions are important quantities for model evaluation and comparisons. We present a new method to compute partition functions of complex an…