2 citations · 3 across the 8 of their papers we have counts for
7 papers · 1 filter
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…
Translating Canonical SQL to Imperative Code in Coq
Véronique Benzaken, Évelyne Contejean, Mohammed Houssem Hachmaoui +4
SQL is by far the most widely used and implemented query language. Yet, on some key features, such as correlated queries and NULL value semantics, many implementations diverge or c…
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…
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…