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SUMMARY:Reactive Probabilistic Programming and Semi-Symbolic Inference - G
 uillaume Baudart (INRIA)
DTSTART:20240820T110000Z
DTEND:20240820T113000Z
UID:TALK219916@talks.cam.ac.uk
DESCRIPTION:Reactive synchronous languages are now a standard industry too
 l for critical embedded systems. Designers write high-level specifications
  by composing streams of values. Such systems typically evolve in noisy en
 vironments that can only be observed through noisy sensors. In this talk\,
  I will present ProbZelus\, a synchronous language extended with probabili
 stic constructs for Bayesian reasoning to model uncertainty. ProbZelus pro
 grams describe state-space models interacting with an observable environme
 nt. At runtime\, an inference engine estimates the parameters of the model
  from observations to produce a stream of distributions. I will then detai
 l the semi-symbolic inference algorithms that we use for efficient streami
 ng inference which combine approximate sampling methods and exact symbolic
  computations.
LOCATION:Seminar Room 1\, Newton Institute
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