[TYPES/announce] [LAFI 2021]: POPL 21 workshop on Languages for Inference

[Jean-Baptiste Tristan]

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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 16, 2020!

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

Deadline: October 16, 2020 (AoE)
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 16, 2020 (AoE)

Submission link: https://lafi21.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.

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Jean-Baptiste Tristan
Associate Professor
Department of Computer Science
Boston College
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