Learn what probabilistic programming is, how it works, and what are some of the best ways to use it for natural language processing tasks. Agree & Join LinkedIn ...

Machine learning (ML) and probabilistic programming are two powerful tools in the arsenal of data science, each with its own strengths. ML excels at making predictions from complex data, while ...

Probabilistic Differential Dynamic Programming (PDDP) is a data-driven, probabilistic trajectory optimization framework for systems with unknown dynamics. This is an implementation of Yunpeng Pan and ...

In this paper, we describe connections this research area called “Probabilistic Programming” has with programming languages and software engineering, and this includes language design, and the static ...

Bayesian inference with probabilistic programming. The Turing Language has 29 repositories available. Follow their code on GitHub. Skip to content. ... Implementation of domain-specific language (DSL) ...

The consideration of reliability in controller design is able to avoid the potential actuator faults from inappropriate strategies. This work presents an optimal reliability-critical controller to ...

Keywords: path-planning, dynamic programming, multi-agent, factor graph, probabilistic inference. Citation: Di Gennaro G, Buonanno A, Fioretti G, Verolla F, Pattipati KR and Palmieri FAN (2022) ...