GRAN VS euler

Compare GRAN vs euler and see what are their differences.

GRAN

Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019 (by lrjconan)
neurips-2019 generative-model deep-generative-model graph-neural-networks graph-generation
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euler

A distributed graph deep learning framework. (by alibaba)
Graph graph-learning network-embedding Deep Learning graph-convolutional-networks graph-neural-networks graphsage random-walk Node2vec graph-embedding Gcn ggnn
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GRAN euler
1 2
450 2,873
- 0.2%
0.0 0.0
9 months ago 8 months ago
C++ C++
MIT License Apache License 2.0
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.

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?
    1 project | /r/cscareerquestionsEU | 2 May 2022
    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.

euler

Posts with mentions or reviews of euler. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-17.

What are some alternatives?

When comparing GRAN and euler you can also consider the following projects:

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"

GraphScope - 🔨 🍇 💻 🚀 GraphScope: A One-Stop Large-Scale Graph Computing System from Alibaba | 一站式图计算系统

molecule-generation - Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation

awesome-graph-classification - A collection of important graph embedding, classification and representation learning papers with implementations.

ProGraML - A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

pytorch_geometric_temporal - PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

libgrape-lite - 🍇 A C++ library for parallel graph processing (GRAPE) 🍇

libvineyard - vineyard (v6d): an in-memory immutable data manager. [Moved to: https://github.com/alibaba/v6d]

efficient-gnns - Code and resources on scalable and efficient Graph Neural Networks

vg - tools for working with genome variation graphs

GNNs-Recipe - 🟠 A study guide to learn about Graph Neural Networks (GNNs)

simulacrum - A framework for procedural content generation with C++20

GRAN vs Generalizing-Lottery-Tickets euler vs GraphScope GRAN vs molecule-generation euler vs awesome-graph-classification GRAN vs ProGraML euler vs pytorch_geometric_temporal euler vs libgrape-lite euler vs libvineyard euler vs efficient-gnns euler vs vg euler vs GNNs-Recipe euler vs simulacrum