The Seventh International Workshop on Languages for InferenceLAFI 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 languages, including ones that incorporate automatic differentiation
• Automatic differentiation algorithms for differentiable programming languages
• Probabilistic generative modelling and inference
• Variational and differential modelling and inference
• Semantics (axiomatic, operational, denotational, games, etc) and types for inference and/or differentiable programming
• Efficient and correct implementation
• Applications of inference and/or differentiable programming

Accepted Papers

Call for Extended Abstracts

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                  Call for Extended Abstracts


                           LAFI 2022
          POPL 2022 workshop on Languages for Inference


                         January 16, 2022
           https://popl22.sigplan.org/home/lafi-2022


            Submission deadline on October 20, 2021 - EXTENDED

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***** Submission Summary *****

Deadline: October 20, 2021 (AoE) - EXTENDED Link: https://lafi22.hotcrp.com/ Format: extended abstract (2 pages + references)

***** Call for Extended Abstracts *****

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 recent rise of practical implementations as well as research activity in inference-based programming has renewed the need for semantics to help us share insights and innovations.

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 inference and/or differentiable programming;

• inference algorithms for probabilistic programming languages, including ones that incorporate automatic differentiation;

• automatic differentiation algorithms for differentiable programming languages;

• probabilistic generative modeling and inference;

• variational and differential modeling and inference;

• semantics (axiomatic, operational, denotational, games, etc) and types for inference and/or differentiable programming;

• efficient and correct implementation;

• and last but not least, applications of inference and/or differentiable programming.

We expect this workshop to be informal, and our goal is to foster collaboration and establish common ground. Thus, the proceedings will not be a formal or archival publication, and we expect to spend only a portion of the workshop day on traditional research talks. Nevertheless, as a concrete basis for fruitful discussions, we call for extended abstracts describing specific and ideally ongoing work on probabilistic and differential programming languages, semantics, and systems.

***** Submission guidelines *****

Submission deadline on October 20, 2021 (AoE) - EXTENDED

Submission link: https://lafi22.hotcrp.com/

Anonymous extended abstracts are up to 2 pages in PDF format, excluding references.

In line with the SIGPLAN Republication Policy, inclusion of extended abstracts in the program is not intended to preclude later formal publication.

• Sam Staton, University of Oxford
• Maria Gorinova, Twitter
• Feras Saad, Massachusetts Institute of Technology
• Hugo Paquet, University of Oxford
• Roy Frostig, Google Research
• Atılım Güneş Baydin, University of Oxford
• Damiano Mazza, Université Sorbonne Paris Nord