POPL 2024
Sun 14 - Sat 20 January 2024 London, United Kingdom

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/

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Plenary
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Sun 14 Jan

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09:00 - 10:30
First SessionLAFI at Kelvin Lecture
Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University
09:00
10m
Talk
Opening Remarks
LAFI

09:10
60m
Keynote
Hong Ge: Bayesian inference using probabilistic programming
LAFI
Hong Ge University of Cambridge
10:10
20m
Talk
Basis Talk
LAFI

10:30 - 11:00
10:30
30m
Coffee break
Break
Catering

10:30 - 11:00
10:30
30m
Coffee break
Break
Catering

11:00 - 12:30
Second SessionLAFI at Kelvin Lecture
Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University
11:00
10m
Talk
A Tree Sampler for Bounded Context-Free Languages
LAFI
Breandan Considine McGill University
File Attached
11:10
10m
Talk
A Multi-language Approach to Probabilistic Program Inference
LAFI
Sam Stites Northeastern University, Steven Holtzen Northeastern University
11:20
10m
Talk
Belief Programming in Partially Observable Probabilistic Environments
LAFI
Tobias Gürtler Saarland University, Saarland Informatics Campus, Benjamin Lucien Kaminski Saarland University; University College London
11:30
10m
Talk
Homomorphic Reverse Differentiation of IterationOnline
LAFI
Fernando Lucatelli Nunes Utrecht University, Gordon Plotkin Google, Matthijs Vákár Utrecht University
File Attached
11:40
10m
Talk
MultiSPPL: extending SPPL with multivariate leaf nodes
LAFI
Matin Ghavami Massachusetts Institute of Technology, Mathieu Huot MIT, Martin C. Rinard Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology
11:50
10m
Talk
Reverse mode ADEV via YOLO: tangent estimators transpose to gradient estimators
LAFI
McCoy Reynolds Becker MIT, Mathieu Huot MIT, Alexander K. Lew Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology
12:00
10m
Talk
Sparse Differentiation in Computer Graphics
LAFI
Kevin Mu University of Washington, Jesse Michel Massachusetts Institute of Technology, William S. Moses Massachusetts Institute of Technology, Shoaib Kamil Adobe Research, Zachary Tatlock University of Washington, Alec Jacobson University of Toronto, Jonathan Ragan-Kelley Massachusetts Institute of Technology
12:10
10m
Talk
A slice sampler for the Indian Buffet Process: expressivity in nonparametric probabilistic programming
LAFI
Maria-Nicoleta Craciun University of Oxford, C.-H. Luke Ong NTU, Hugo Paquet LIPN, Université Sorbonne Paris Nord, Sam Staton University of Oxford
12:20
10m
Talk
Effective Sequential Monte Carlo for Language Model Probabilistic Programs
LAFI
Alexander K. Lew Massachusetts Institute of Technology, Tan Zhi-Xuan Massachusetts Institute of Technology, Gabriel Grand Massachusetts Institute of Technology, Jacob Andreas MIT, Vikash K. Mansinghka Massachusetts Institute of Technology
12:30 - 14:00
12:30
90m
Lunch
Lunch
Catering

12:30 - 14:00
12:30
90m
Lunch
Lunch
Catering

14:00 - 15:30
Third SessionLAFI at Kelvin Lecture
Chair(s): Steven Holtzen Northeastern University, Matthijs Vákár Utrecht University
14:00
10m
Talk
Effect Handlers for Choice-Based Learning
LAFI
Gordon Plotkin Google, Ningning Xie University of Toronto
File Attached
14:10
10m
Talk
Guaranteed Bounds for Discrete Probabilistic Programs with Loops via Generating Functions
LAFI
Fabian Zaiser University of Oxford, Andrzej Murawski University of Oxford, C.-H. Luke Ong NTU
File Attached
14:20
10m
Talk
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
10m
Talk
Mixture Languages
LAFI
Oliver Richardson Cornell University, Jialu Bao Cornell University
File Attached
14:40
10m
Talk
Structured Tensor Algebra for Efficient Discrete Probabilistic Inference
LAFI
Amir Shaikhha University of Edinburgh
14:50
10m
Talk
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
10m
Talk
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
10m
Talk
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
10m
Talk
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
30m
Coffee break
Break
Catering

15:30 - 16:00
15:30
30m
Coffee 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

Title
Abstract Interpretation for Automatic DifferentiationOnline
LAFI
A Multi-language Approach to Probabilistic Program Inference
LAFI
A slice sampler for the Indian Buffet Process: expressivity in nonparametric probabilistic programming
LAFI
A Tree Sampler for Bounded Context-Free Languages
LAFI
File Attached
Bayesian inference using probabilistic programming
LAFI
Belief Programming in Partially Observable Probabilistic Environments
LAFI
Effect Handlers for Choice-Based Learning
LAFI
File Attached
Effective Sequential Monte Carlo for Language Model Probabilistic Programs
LAFI
Guaranteed Bounds for Discrete Probabilistic Programs with Loops via Generating Functions
LAFI
File Attached
Homomorphic Reverse Differentiation of IterationOnline
LAFI
File Attached
JuliaBUGS: A Graph-Based Probabilistic Programming Language using BUGS syntax
LAFI
Mixture Languages
LAFI
File Attached
MultiSPPL: extending SPPL with multivariate leaf nodes
LAFI
Reverse mode ADEV via YOLO: tangent estimators transpose to gradient estimators
LAFI
Sparse Differentiation in Computer Graphics
LAFI
Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial SolvingOnline
LAFI
Structured Tensor Algebra for Efficient Discrete Probabilistic Inference
LAFI
Toward Probabilistic Coarse-to-Fine Program Synthesis
LAFI
Towards a Categorical Model of the Lilac Separation Logic
LAFI
File Attached

Call for Papers

=====================================================================

             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 

=====================================================================

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.

Questions? Use the LAFI contact form.