LAFI

LAFI 2025 with POPL 2025

The Languages for Inference (LAFI) workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: Design of programming languages for statistical inference and/or differentiable programming Inference algorithms for probabilistic programming languages, including ones that incorporate automatic di ...

LAFI 2024 with POPL 2024

The Languages for Inference (LAFI) workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: Design of programming languages for statistical inference and/or differentiable programming Inference algorithms for probabilistic programming languages, including ones that incorporate automatic di ...

LAFI 2023 with POPL 2023

The Languages for Inference (LAFI) workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: Design of programming languages for statistical inference and/or differentiable programming Inference algorithms for probabilistic programming languages, including ones that incorporate automatic di ...

LAFI 2022 with POPL 2022

NEWS LAFI 2022 will be a purely virtual event. Detailed schedule to be posted soon. This workshop aims to bring programming-language and machine-learning researchers together to advance all aspects of languages for inference. Topics include but are not limited to: Design of programming languages for statistical inference and/or differentiable programming Inference algorithms for probabilistic programming ...

LAFI 2021 with POPL 2021

Inference concerns re-calibrating program parameters based on observed data, and has gained wide traction in machine learning and data science. Inference can be driven by probabilistic analysis and simulation, and through back-propagation and differentiation. Languages for inference offer built-in support for expressing probabilistic models and inference methods as programs, to ease reasoning, use, and reuse. The ...

LAFI 2020 with POPL 2020

Invited speaker Fritz Obermeyer, Uber AI Labs Nonstandard Interpretation in Pyro About LAFI Inference concerns re-calibrating program parameters based on observed data, and has gained wide traction in machine learning and data science. Inference can be driven by probabilistic analysis and simulation, and through back-propagation and differentiation. Languages for inference offer built-in support for expr ...

LAFI 2019 with POPL 2019

Inference concerns re-calibrating program parameters based on observed data, and has gained wide traction in machine learning and data science. Inference can be driven by probabilistic analysis and simulation, and through back-propagation and differentiation. Languages for inference offer built-in support for expressing probabilistic models and inference methods as programs, to ease reasoning, use, and reuse. The ...

PPS 2018 with POPL 2018

Program We are excited to announce our 2018 program, including an invited talk, an invited tutorial, and the following talks and posters. For more details on the schedule, see the Program tab. The extended abstracts for the talks and posters can be found at http://pps2018.soic.indiana.edu Join our slack discussion at https://popl2018.slack.com/#pps Invited talk Erik Meijer, Facebook Software is eating the wo ...

PPS 2017 with POPL 2017

Workshop on probabilistic programming semantics Probabilistic programming is the idea of expressing probabilistic models and inference methods as programs, to ease use and reuse. The recent rise of practical implementations as well as research activity in probabilistic programming has renewed the need for semantics to help us share insights and innovations. This workshop aims to bring programming-language and m ...

PPS 2016 with POPL 2016