Workshop dinner registration
We are grateful to our sponsor Basis for hosting a workshop dinner. Please register here: https://lu.ma/vjtutz5l .
Scope of the workshop
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
Invited speakers
We are pleased to have the following two invited talks this year:
- Desi R. Ivanova (University of Oxford) – Modern Bayesian experimental design
- Jonathan Citrin (Google Deepmind) – TORAX: A Fast and Differentiable Tokamak Transport Simulator in JAX
Schedule
The workshop will take place during the full day of Sunday 19 January 2025. It will consist of a series of submitted talks (of roughly 15min each) and invited talks, as well as an interactive poster session. We will conclude the day with a dinner/drinks event. A detailed schedule will appear here shortly.
Sponsorship
LAFI is grateful to be sponsored this year by Basis https://www.basis.ai/
This program is tentative and subject to change.
Sun 19 JanDisplayed time zone: Mountain Time (US & Canada) change
11:00 - 12:30 | |||
11:00 40mTalk | Invited talk: TORAX - A Fast and Differentiable Tokamak Transport Simulator in JAX (Remote) LAFI Jonathan Citrin Google Deepmind | ||
11:41 15mTalk | Data-Parallel Differentiation by Optic Composition LAFI | ||
11:57 15mTalk | Data-oriented Design for Differentiable, Probabilistic Programming (Remote) LAFI Owen Lynch University of Oxford, Maria-Nicoleta Craciun University of Oxford, Younesse Kaddar University of Oxford, Sam Staton University of Oxford | ||
12:13 15mTalk | A Domain-Specific PPL for Reasoning about Reasoning (or: a memo on memo) LAFI Kartik Chandra MIT, Tony Chen MIT, Joshua B. Tenenbaum Massachusetts Institute of Technology, Jonathan Ragan-Kelley Massachusetts Institute of Technology |
12:30 - 14:00 | |||
12:30 90mLunch | Lunch Catering |
14:00 - 15:30 | |||
14:00 40mTalk | Invited talk: Modern Bayesian Experimental Design LAFI Desi R. Ivavona University of Oxford | ||
14:41 15mTalk | Semantics of the memo Probabilistic Programming Language LAFI | ||
14:57 15mTalk | NP-NUTS: A Nonparametric No-U-Turn Sampler LAFI Maria-Nicoleta Craciun University of Oxford, C.-H. Luke Ong NTU, Sam Staton University of Oxford, Matthijs Vákár Utrecht University | ||
15:13 15mTalk | Sandwood: Runtime Adaptable Probabilistic Programming for Java (Remote) LAFI File Attached |
16:00 - 17:30 | |||
16:00 15mTalk | Partially Evaluating Higher-Order Probabilistic Programs without Stochastic Recursion to Graphical Models (Remote) LAFI | ||
16:16 15mTalk | State Space Model Programming in Turing.jl LAFI Tim Hargreaves Department of Engineering, University of Cambridge, Qing Li Department of Engineering, University of Cambridge, Charles Knipp Federal Reserve Board of Governors, USA, Frederic Wantiez , Simon J. Godsill Department of Engineering, University of Cambridge, Hong Ge University of Cambridge File Attached | ||
16:32 55mOther | Poster session LAFI | ||
17:28 2mDay closing | Closing remarks LAFI Atılım Güneş Baydin University of Oxford |
Accepted Papers
Call for Papers
=====================================================================
Call for Extended Abstracts
LAFI 2025
Workshop on Languages for Inference at POPL 2025
January 19, 2025
https://popl25.sigplan.org/home/lafi-2025
Submission Deadline: October 30, 2024
=====================================================================
Submission Summary
- Deadline: October 30, 2024 (AoE)
- Submission page: https://lafi25.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 30, 2024 (AoE)
- Submission link: https://lafi25.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.