Homomorphic Reverse Differentiation of Iteration (LAFI 2024) - POPL 2024

Sun 14 - Sat 20 January 2024 London, United Kingdom

Who

Fernando Lucatelli Nunes, Gordon Plotkin, Matthijs Vákár

Track

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When

Sun 14 Jan 2024 11:30 - 11:40 at Kelvin Lecture - Second Session Chair(s): Steven Holtzen, Matthijs Vákár

Abstract

We describe how homomorphic reverse mode AD (to be precise, the CHAD method) applies to partial programs with iteration (unbounded looping) constructs. The solution is surprisingly simple and beautiful from a mathematical point of view, arising from a universal property, and it leads to efficient and compositional implementations.

File attachments

Extended Abstract (PDF.pdf)	430KiB

Fernando Lucatelli Nunes

Utrecht University

Gordon Plotkin

Google

Matthijs Vákár

Utrecht University

Time Zone

The program is currently displayed in (GMT) London.

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Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
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Session Program

Sun 14 Jan
Displayed time zone: London change

	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