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Found 5 papers, 3 papers with code
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
We prove that MC-EIF is consistent, and that estimators using MC-EIF achieve optimal $\sqrt{N}$ convergence rates.
Functional Tensors for Probabilistic Programming
It is a significant challenge to design probabilistic programming systems that can accommodate a wide variety of inference strategies within a unified framework.
Variational Bayesian Optimal Experimental Design
Bayesian optimal experimental design (BOED) is a principled framework for making efficient use of limited experimental resources.
Tensor Variable Elimination for Plated Factor Graphs
To exploit efficient tensor algebra in graphs with plates of variables, we generalize undirected factor graphs to plated factor graphs and variable elimination to a tensor variable elimination algorithm that operates directly on plated factor graphs.
Pyro: Deep Universal Probabilistic Programming
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research.
