8 citations · 24 across the 14 of their papers we have counts for
9 papers · 1 filter
PoTo: A Hybrid Andersen's Points-to Analysis for Python
Ingkarat Rak-amnouykit, Ana Milanova, Guillaume Baudart +2
As Python is increasingly being adopted for large and complex programs, the importance of static analysis for Python (such as type inference) grows. Unfortunately, static analysis…
Inference Plans for Hybrid Particle Filtering
Ellie Y. Cheng, Eric Atkinson, Guillaume Baudart +2
Advanced probabilistic programming languages (PPLs) using hybrid particle filtering combine symbolic exact inference and Monte Carlo methods to improve inference performance. These…
Density-Based Semantics for Reactive Probabilistic Programming
Guillaume Baudart, Louis Mandel, Christine Tasson
Synchronous languages are now a standard industry tool for critical embedded systems. Designers write high-level specifications by composing streams of values using block diagrams.…
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…
Automatic Guide Generation for Stan via NumPyro
Guillaume Baudart, Louis Mandel
Stan is a very popular probabilistic language with a state-of-the-art HMC sampler but it only offers a limited choice of algorithms for black-box variational inference. In this pap…
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…
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…
Yaps: Python Frontend to Stan
Guillaume Baudart, Martin Hirzel, Kiran Kate +2
Stan is a popular probabilistic programming language with a self-contained syntax and semantics that is close to graphical models. Unfortunately, existing embeddings of Stan in Pyt…