[TYPES/announce] LAFI'21, Workshop on Languages for Inference: extended deadline

[Jean-Baptiste Tristan]

The deadline to submit to the 2021 Languages for Inference workshop
(affiliated with POPL'21) was extended until October 30, 2020.


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                 Call for Extended Abstracts

                          LAFI 2021
         POPL 2021 workshop on Languages for Inference

                        January 17, 2021
          https://popl21.sigplan.org/home/lafi-2021

           Submission deadline on October 30, 2020 (extended).

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

Deadline: October 30, 2020 (extended)

Link: https://lafi21.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.

Two years ago, we explicitly expanded the focus of the workshop from
statistical probabilistic programming to encompass differentiable
programming for statistical machine learning. This change seemed
well-received by the community, and we want to continue it this year in an
effort to extend the strong ties between programming language-based machine
learning and the POPL community.

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 30, 2020 (extended).

Submission link: https://lafi21.hotcrp.com/

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.
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