LAFI 2024
| title | author | length |
|---|---|---|
| Opening Remarks | 02m | |
Agenda and logistics for the day: 18 presentations and workshops run as 10-minute talks with strict timing, plus a 90-minute poster session at day’s end for… | ||
| Basis Talk: Reasoning via Semantic Transformations | Zen tovaris | 26m |
Describes a working system Cairo (built on Pyro) that runs SIR ODE models, performs Bayesian posterior inference (variational first, MCMC supported), and… | ||
| A Tree Sampler for Bounded Context-Free Languages | Breandan Considine | 09m |
Claims a practical method to enumerate and sample distinct parse trees from bounded context-free languages by building an algebraic tree datatype that… | ||
| A Multi-language Approach to Probabilistic Program Inference | Sam Stites, Steven Holtzen | 08m |
Claims a first probabilistic multilanguage that composes languages with different inference runtimes (example: Dice for discrete, Pyro for continuous) by… | ||
| Belief Programming in Partially Observable Probabilistic Environments | Tobias Gürtler, Benjamin Lucien Kaminski | 08m |
The work introduces P-BLIMP, a probabilistic belief-programming language with true/observe/infer statements that maintain belief states as probability… | ||
| Homomorphic Reverse Differentiation of Iteration | Fernando Lucatelli Nunes, Gordon Plotkin, Matthijs I. L. Vákár | 10m |
Claims that CHAD applies to partial programs with iteration by moving CHAD into a categorical target (the free completion on the dual of Vect with ωCPO… | ||
| MultiSPPL: extending SPPL with multivariate leaf nodes | Matin Ghavami, Mathieu Huot, Martin C. Rinard, Vikash K. Mansinghka | 09m |
Claims that extending SPPL’s SPN leaves with a SPINNY interface of five methods (sample, PDF, prop, condition, constrain) guarantees closure under conditioning… | ||
| Reverse mode ADEV via YOLO: tangent estimators transpose to gradient estimators | McCoy R. Becker, Mathieu Huot, Alexander K. Lew, Vikash K. Mansinghka | 10m |
Claims an automated pipeline that converts ADEV's forward-mode tangent estimators into a reverse-mode estimator by applying YOLO’s unzip and transposition… | ||
| A slice sampler for the Indian Buffet Process: expressivity in nonparametric pro... | Maria-Nicoleta Crăciun, C.-H. Luke Ong, Hugo Paquet, Sam Staton | 09m |
Introduces a slice-sampling construction that encodes the Indian Buffet Process inside a pure probabilistic program without truncation or hidden state, by… | ||
| Effective Sequential Monte Carlo for Language Model Probabilistic Programs | Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand, Jacob Andreas, Vikash K. Mansinghka | 11m |
LLaMPPL implements Sequential Monte Carlo for language-model probabilistic programs, using SMC with auto-batching of LLM calls and activation caching to run… | ||
| Effect Handlers for Choice-Based Learning | Gordon Plotkin, Ningning Xie | 14m |
Combines algebraic effects and handlers with loss continuations to make choice points first-class for optimizing decisions. Shows a Haskell effect-handler… | ||
| Guaranteed Bounds for Discrete Probabilistic Programs with Loops via Generating ... | Fabian Zaiser, Andrzej S. Murawski, C.-H. Luke Ong | 10m |
Technique finds guaranteed upper and lower bounds on the posterior of discrete probabilistic programs with unbounded loops by representing distributions as… | ||
| JuliaBUGS: A Graph-Based Probabilistic Programming Language using BUGS syntax | Xianda Sun, Philipp Gabler, Andrew Thomas, Hong Ge | 10m |
JuliaBUGS.jl implements the classic BUGS syntax as a Julia package and represents models as explicit computation graphs so inference engines can operate on the… | ||
| Mixture Languages | Oliver Richardson, Jialu Bao | 10m |
Claim of a general-purpose continuous-process programming language with a native notion of parallel composition: states are topological manifolds, semantics… | ||
| Structured Tensor Algebra for Efficient Discrete Probabilistic Inference | Amir Shaikhha | 10m |
An implementation of Buck in Julia called JuliaBux extends the Buck language with external functions and a Julia macro, exposes log‑density and gradients, and… | ||
| Towards a Categorical Model of the Lilac Separation Logic | John Li, Jon M. Aytac, Philip Johnson-Freyd, Amal Ahmed, Steven Holtzen | 08m |
Constructs two categories—a probabilistic “sheaf/topos–style” category and a nominal-style category—and proves they are equivalent, so Lilac’s independent… | ||
| Toward Probabilistic Coarse-to-Fine Program Synthesis | Maddy Bowers, Alexander K. Lew, Vikash K. Mansinghka, Joshua B. Tenenbaum, Armando Solar-Lezama | 12m |
Synthesizes programs by starting with coarse probabilistic programs that use randomness as placeholders, then iteratively refines high-entropy expressions into… | ||
| Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial ... | Peixin Wang, Hongfei Fu, Tengshun Yang, Guanyan Li, C.-H. Luke Ong | 11m |
Automated method derives guaranteed upper and lower bounds on a probabilistic program’s normalized posterior by reducing NPD bounding to bounds on the… | ||
| Abstract Interpretation for Automatic Differentiation | Jacob Laurel, Siyuan Brant Qian, Gagandeep Singh, Sasa Misailovic | 11m |
Static analysis produces sound numeric bounds on derivatives computed by AD, using a synthesized abstract interpreter that encloses nonlinear patterns with a… | ||
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