Deep Learning As Program Synthesis

Deep Learning As Program Synthesis Information Guide

1. Background to Deep Learning As Program Synthesis
2. Key Details
3. History
4. Expert Insights
5. Final Thoughts

Background to Deep Learning As Program Synthesis

In the SLT seminar, Zach Furman from The University of Melbourne discusses evidence for Course webpage: With the advancement of modern technologies, Kevin Ellis (Cornell) and Zenna Tavares (BASIS) argue that the next wave of AI needs to learn like humans do: building abstract ... Panel discussion with Francois Chollet, Kevin Ellis, and Zenna Tavares on why ההרצאה הייתה חלק מאירוע CodeAI של קהילת MDLI ו-Intuit This lecture presents a hybrid approach of ... fields and leading to rapidly maturing tools both in

Authors: Rohan Bavishi, Caroline Lemieux, Roy Fox, Koushik Sen, Ion Stoica Presented at SPLASH 2019.

Key Details

History

SYNT 2020: Neuro-Symbolic Program Synthesis from Natural Language and Demonstrations

Software Synthesis Using Large Language Models and Genetic Algorithm

Advanced Machine Learning Day 3: Neural Program Synthesis

Neurosymbolic Programming - Yisong Yue

Program Synthesis via Deep Learning over Graph Structured Data

[PLDI'25] Neurosymbolic Program Synthesis: Bridging Perception and Reasoning in Real-World(…)

AutoPandas: Neural-Backed Generators for Program Synthesis

Neural Program Synthesis for Navigation and Language Understanding | Xinyun Chen

Neural Program Synthesis

Expert Insights

Data is compiled from public records and verified media reports.

Last Updated: June 22, 2026

Final Thoughts

Disclaimer: Disclaimer: Details estimates are based on publicly available data, media reports, and financial analysis. Actual numbers may vary.