6 citations · 9 across the 4 of their papers we have counts for
4 papers
A Bayesian Approach to Membership Inference for Statistical Release
Lisa Oakley, Sam Stites, Cameron Moy +3
The membership inference problem for publicly released statistics from a private dataset is well-studied. When developing and formally analyzing attack strategies, however, the foc…
Multi-Language Probabilistic Programming
Sam Stites, John M. Li, Steven Holtzen
There are many different probabilistic programming languages that are specialized to specific kinds of probabilistic programs. From a usability and scalability perspective, this is…
Nested Variational Inference
Heiko Zimmermann, Hao Wu, Babak Esmaeili +1
We develop nested variational inference (NVI), a family of methods that learn proposals for nested importance samplers by minimizing an forward or reverse KL divergence at each lev…
Learning Proposals for Probabilistic Programs with Inference Combinators
Sam Stites, Heiko Zimmermann, Hao Wu +2
We develop operators for construction of proposals in probabilistic programs, which we refer to as inference combinators. Inference combinators define a grammar over importance sam…