Introduction on Program Synthesis Via Deep Learning Over Graph Structured Data
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Neural Program Synthesis
Program Synthesis meets Notebooks
Interpretable Program Synthesis
Program Synthesis for Data Science
Gauss: Program Synthesis by Reasoning Over Graphs
Osbert Bastani - Interpretable Machine Learning via Program Synthesis - IPAM at UCLA
Deep Learning on Graphs | Prerequisites
Neural Network guided Grammar Filtering For Syntax-Guided Synthesis
Robot Action Selection Learning via Dimension Informed Program Synthesis: CORL2020
Program Synthesis as High-Level Machine Learning Swarat Chaudhuri | FLOC 2018
[ICCAD'20] Accurate Operation Delay Prediction for FPGA HLS Using Graph Neural Networks
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Last Updated: October 2, 2026
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Mayur Naik (University of Pennsylvania) simons.berkeley.edu/talks/tbd-297 Talk by Nathanael Fijalkow in the IARCS Verification Seminar Series, Huizhao Wang, Hikvision Research Institute Considering that each node has its own characteristics, we believe Денис Ракитин, НИУ ВШЭ The problem of Talk by Rohan Bavishi in the IARCS Verification Seminar Series, While input-output examples are a natural form of specification for Recorded 10 January 2023. Osbert Bastani of the University of Pennsylvania presents "Interpretable youtube.com/watch?v=AiasD4ZxzcY&list=PLLlTVphLQsuOS1XwHGLW8j2NVtXvhaa76 Before diving into advanced ... Mark Santolucito (Barnard College) ... CORL2020 Video Presentation Paper Link: arxiv.org/abs/2008.04133. Presented by Ecenur Ustun at ICCAD2020, online. Abstract: Modern heterogeneous FPGA architectures incorporate a variety of ...
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