6 citations · 15 across the 5 of their papers we have counts for
7 papers
Verifying Performance Properties of Probabilistic Inference
Eric Atkinson, Ellie Y. Cheng, Guillaume Baudart +2
In this extended abstract, we discuss the opportunity to formally verify that inference systems for probabilistic programming guarantee good performance. In particular, we focus on…
Semi-Symbolic Inference for Efficient Streaming Probabilistic Programming
Eric Atkinson, Charles Yuan, Guillaume Baudart +2
Efficient inference is often possible in a streaming context using Rao-Blackwellized particle filters (RBPFs), which exactly solve inference problems when possible and fall back on…
Statically Bounded-Memory Delayed Sampling for Probabilistic Streams
Eric Atkinson, Guillaume Baudart, Louis Mandel +2
Probabilistic programming languages aid developers performing Bayesian inference. These languages provide programming constructs and tools for probabilistic modeling and automated…
Programming and Reasoning with Partial Observability
Eric Atkinson, Michael Carbin
Computer programs are increasingly being deployed in partially-observable environments. A partially observable environment is an environment whose state is not completely visible t…
Simplifying Dependent Reductions in the Polyhedral Model
Cambridge Yang, Eric Atkinson, Michael Carbin
A Reduction -- an accumulation over a set of values, using an associative and commutative operator -- is a common computation in many numerical computations, including scientific c…
Reactive Probabilistic Programming
Guillaume Baudart, Louis Mandel, Eric Atkinson +3
Synchronous modeling is at the heart of programming languages like Lustre, Esterel, or Scade used routinely for implementing safety critical control software, e.g., fly-by-wire and…