PDN VS awesome-graph-classification

Compare PDN vs awesome-graph-classification and see what are their differences.

PDN

The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21) (by benedekrozemberczki)
Gcn Gnn Deepwalk Multiplex Graph2vec Pytorch graph-neural-network Deep Learning pathfinder message-passing neural-message-passing cheminformatics molecules graph-classification node-classification network-science Data Science Transformer Bert gpt-3
Source Code
arxiv.org
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awesome-graph-classification

A collection of important graph embedding, classification and representation learning papers with implementations. (by benedekrozemberczki)
Graph2vec classification-algorithm graph-kernels weisfeiler-lehman kernel-methods deep-graph-kernels netlsd graph-attention-model graph-attention-networks structural-attention attention-mechanism graph-kernel Node2vec graph-embedding network-embedding node-embedding graph-representation-learning Deepwalk graph-convolutional-networks graph-classification
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PDN awesome-graph-classification
1 1
57 4,698
- -
0.0 1.0
over 1 year ago about 1 year ago
Python Python
GNU General Public License v3.0 only Creative Commons Zero v1.0 Universal
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.

PDN

Posts with mentions or reviews of PDN. We have used some of these posts to build our list of alternatives and similar projects.

awesome-graph-classification

Posts with mentions or reviews of awesome-graph-classification. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing PDN and awesome-graph-classification you can also consider the following projects:

gnn - TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

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

pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]

euler - A distributed graph deep learning framework.

gnn-lspe - Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022

GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)

karateclub - Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

GraphGPS - Recipe for a General, Powerful, Scalable Graph Transformer

awesome-drug-pair-scoring - Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)

PDN vs gnn awesome-graph-classification vs pytorch_geometric_temporal PDN vs pytorch-lightning awesome-graph-classification vs euler PDN vs gnn-lspe awesome-graph-classification vs GAT PDN vs karateclub awesome-graph-classification vs karateclub PDN vs best-of-ml-python awesome-graph-classification vs GraphGPS PDN vs pytorch_geometric_temporal PDN vs awesome-drug-pair-scoring