Interpretable Program Synthesis Information Guide

  1. Overview on Interpretable Program Synthesis
  2. Important Facts
  3. History
  4. Deep Dive
  5. Future Outlook

Overview on Interpretable Program Synthesis

Details Interpretable Program Synthesis Guide
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Important Facts

Interpretable Program Synthesis Guide
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History

Information Exploring Program Synthesis: Francois Chollet, Kevin Ellis, Zenna Tavares Update
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Why Program Synthesis Is Next (Kevin Ellis and Zenna Tavares)
Why Program Synthesis Is Next (Kevin Ellis and Zenna Tavares)
Interactive Program Synthesis by Augmented Examples
Interactive Program Synthesis by Augmented Examples
Gabe Grand | LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabe Grand | LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Armando Solar Lezama - AI Programming; Program Synthesis • YASP #3
Armando Solar Lezama - AI Programming; Program Synthesis • YASP #3
Relational Decomposition for Program Synthesis - Céline Hocquette
Relational Decomposition for Program Synthesis - Céline Hocquette
Dreamcoder: Bootstrapping Inductive Program Synthesis With Wake-Sleep Library Learning
Dreamcoder: Bootstrapping Inductive Program Synthesis With Wake-Sleep Library Learning
UIST 2020 Interactive Program Synthesis Preview
UIST 2020 Interactive Program Synthesis Preview
Demo: Interactive Program Synthesis by Augmented Examples (UIST 2020)
Demo: Interactive Program Synthesis by Augmented Examples (UIST 2020)
Program Synthesis via Deep Learning over Graph Structured Data
Program Synthesis via Deep Learning over Graph Structured Data
An Introduction to (Inductive) Program Synthesis, by Ali Shokri
An Introduction to (Inductive) Program Synthesis, by Ali Shokri
Interpretability via Compositionality (Wolfgang Stammer) - Interpretable Deep Learning Seminars
Interpretability via Compositionality (Wolfgang Stammer) - Interpretable Deep Learning Seminars

Deep Dive

Data is compiled from public records and verified media reports.

Last Updated: September 22, 2026

Future Outlook

Details Osbert Bastani - Interpretable Machine Learning via Program Synthesis - IPAM at UCLA Guide
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Disclaimer: Disclaimer: All information is compiled from publicly available data, media reports, and analysis. Actual details may vary.

Summary

Interpretable Program Synthesis Panel discussion with Francois Chollet, Kevin Ellis, and Zenna Tavares on why Recorded 10 January 2023. Osbert Bastani of the University of Pennsylvania presents " Kevin Ellis (Cornell) and Zenna Tavares (BASIS) argue that the next wave of AI needs to learn humans do: building abstract ... Armando Solar-Lezama is a professor of Electrical Engineering and Computer Science and Associate Director and COO of the ... The way a problem is represented can determine whether it is solvable at all. Céline Hocquette, AI researcher at Ndea and former ... Mayur Naik (University of Pennsylvania) simons.berkeley.edu/talks/tbd-297 In this lecture, I'm providing an introduction to Vision-Language Programs learn compositional concepts directly from examples via

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