ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

23 March 2020

Papers citing "ProGraML: Graph-based Deep Learning for Program Optimization and Analysis"

6 / 6 papers shown

Title
Learning to Parallelize in a Shared-Memory Environment with Transformers Reém Harel Yuval Pinter Gal Oren 32 17 0 27 Apr 2022
Federated Data Science to Break Down Silos [Vision] Essam Mansour Kavitha Srinivas K. Hose FedML AI4CE 17 8 0 25 Nov 2021
How could Neural Networks understand Programs? Dinglan Peng Shuxin Zheng Yatao Li Guolin Ke Di He Tie-Yan Liu NAI 8 61 0 10 May 2021
Proof Artifact Co-training for Theorem Proving with Language Models Jesse Michael Han Jason M. Rute Yuhuai Wu Edward W. Ayers Stanislas Polu AIMat 8 120 0 11 Feb 2021
A Literature Study of Embeddings on Source Code Zimin Chen Monperrus Martin 43 82 0 05 Apr 2019
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 243 7,597 0 03 Jul 2012