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 differentiation
- Automatic differentiation algorithms for differentiable programming languages
- Probabilistic generative modelling 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
- Applications of inference and/or differentiable programming
** Sponsorship **
LAFI is grateful to be sponsored this year by basis.ai https://www.basis.ai/
Sun 14 JanDisplayed time zone: London change
09:00 - 10:30 | First SessionLAFI at Kelvin Lecture Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University | ||
09:00 10mTalk | Opening Remarks LAFI | ||
09:10 60mKeynote | Hong Ge: Bayesian inference using probabilistic programming LAFI Hong Ge University of Cambridge | ||
10:10 20mTalk | Basis Talk LAFI |
10:30 - 11:00 | |||
10:30 30mCoffee break | Break Catering |
10:30 - 11:00 | |||
10:30 30mCoffee break | Break Catering |
12:30 - 14:00 | |||
12:30 90mLunch | Lunch Catering |
12:30 - 14:00 | |||
12:30 90mLunch | Lunch Catering |
14:00 - 15:30 | Third SessionLAFI at Kelvin Lecture Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University | ||
14:00 10mTalk | Effect Handlers for Choice-Based Learning LAFI File Attached | ||
14:10 10mTalk | Guaranteed Bounds for Discrete Probabilistic Programs with Loops via Generating Functions LAFI File Attached | ||
14:20 10mTalk | JuliaBUGS: A Graph-Based Probabilistic Programming Language using BUGS syntax LAFI Xianda Sun University of Cambridge, Philipp Gabler Independent researcher, Andrew Thomas University of Cambridge, Hong Ge University of Cambridge | ||
14:30 10mTalk | Mixture Languages LAFI File Attached | ||
14:40 10mTalk | Structured Tensor Algebra for Efficient Discrete Probabilistic Inference LAFI Amir Shaikhha University of Edinburgh | ||
14:50 10mTalk | Towards a Categorical Model of the Lilac Separation Logic LAFI John Li Northeastern University, Jon Aytac Sandia National Laboratories, Philip Johnson-Freyd Sandia National Laboratories, Amal Ahmed Northeastern University, USA, Steven Holtzen Northeastern University File Attached | ||
15:00 10mTalk | Toward Probabilistic Coarse-to-Fine Program Synthesis LAFI Maddy Bowers Massachusetts Institute of Technology, Alexander K. Lew Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology, Joshua B. Tenenbaum Massachusetts Institute of Technology, Armando Solar-Lezama Massachusetts Institute of Technology | ||
15:10 10mTalk | Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial SolvingOnline LAFI Peixin Wang University of Oxford, Hongfei Fu Shanghai Jiao Tong University, Tengshun Yang SKLCS, Institute of Software, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Guanyan Li University of Oxford, C.-H. Luke Ong NTU | ||
15:20 10mTalk | Abstract Interpretation for Automatic DifferentiationOnline LAFI Jacob Laurel University of Illinois at Urbana-Champaign, Siyuan Brant Qian University of Illinois at Urbana-Champaign; Zhejiang University, Gagandeep Singh University of Illinois at Urbana-Champaign; VMware Research, Sasa Misailovic University of Illinois at Urbana-Champaign |
15:30 - 16:00 | |||
15:30 30mCoffee break | Break Catering |
15:30 - 16:00 | |||
15:30 30mCoffee break | Break Catering |
16:00 - 17:30 | Poster and Interactive SessionLAFI at Kelvin Lecture Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University Poster session taking place in the same room as the workshop. | ||
Not scheduled yet
Not scheduled yet Talk | Bayesian inference using probabilistic programming LAFI Hong Ge University of Cambridge |
Accepted Papers
Call for Papers
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Call for Extended Abstracts
LAFI 2024
Tenth Workshop on Languages for Inference at POPL 2024
January 14, 2024
https://popl24.sigplan.org/home/lafi-2024
Submission Deadline: October 27, 2023
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Invited Speaker
Hong Ge, Principal Investigator, Machine Learning Group, University of Cambridge
Submission Summary
- Deadline: October 27, 2023 (AoE)
- Submission page: https://lafi24.hotcrp.com/
- Format: extended abstract (2 pages + references + optional appendices)
- Call for Extended Abstracts
Workshop Goals
LAFI 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:
- The 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;
- Semantics (axiomatic, operational, denotational, games, etc) and types for inference and/or differentiable programming;
- Formal verification and correctness for differentiable and probabilistic programs;
- Applications of inference and/or differentiable programming.
The workshop is informal, and our goal is to foster collaboration and establish a shared foundation for research on languages for inference. 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.
Submission guidelines
- Submission deadline on October 27, 2023 (AoE)
- Submission link: https://lafi24.hotcrp.com/
- Any format is permitted, uploads must be in PDF.
- Page limit: 2 pages of main content, unlimited number of references and appendices. Reviewers are not required or expected to read appendices.
- Anonymity: submissions should be anonymized for peer review.
- In line with the SIGPLAN Republication Policy, inclusion of extended abstracts in the program should not preclude later formal publication.
Remote participation policy
Coordination with the POPL conference is underway to enable remote participation. We strive to create an inclusive environment that does not demand traveling for presenters or participants.