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This conference talk presents Sandwood, an open-source, type-safe probabilistic programming language, compiler, and runtime designed for Java. Learn about this innovative tool that aims to simplify the integration of Bayesian models into applications by providing a familiar language for developers while leveraging the comprehensive model view available to compiled languages. Discover how Bayesian models written in Sandwood are compiled to Java classes that can be instantiated as objects, with each object representing a model instance. Explore how these instances can be configured to target different hardware and execution models, with configurations that can be updated during the object's lifetime. Presented remotely at the LAFI workshop on January 19, 2025, by Daniel Goodman, Adam Pocock, and Natalia Kosilova from Oracle Labs, this 19-minute talk offers valuable insights into making probabilistic programming more accessible to Java developers.
