GRAN
Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019 (by lrjconan)
ProGraML
A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations (by ChrisCummins)
GRAN | ProGraML | |
---|---|---|
1 | 1 | |
451 | 286 | |
- | - | |
0.0 | 3.8 | |
9 months ago | 10 months ago | |
C++ | C++ | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
GRAN
Posts with mentions or reviews of GRAN.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Software Engineering or AI or Data Science?
In your case, I would really avoid AI ML DS altogether unless you believe you have the theoretical prerequisites. The coding part in AI ML DS is not like your typical software. It is scientific code and you must understand what's going on in your program with respect to trainable parameters. Here is an example.
ProGraML
Posts with mentions or reviews of ProGraML.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Cannot Install a Python Package
I want to install the package existing in this repository in my anaconda enviroment https://github.com/ChrisCummins/ProGraML
What are some alternatives?
When comparing GRAN and ProGraML you can also consider the following projects:
euler - A distributed graph deep learning framework.
mewa - Compiler-compiler for writing compiler frontends with Lua
Generalizing-Lottery-Tickets - This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers"
molecule-generation - Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation