benchmarking-gnns
Repository for benchmarking graph neural networks (by graphdeeplearning)
graphtransformer
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21. (by graphdeeplearning)
| benchmarking-gnns | graphtransformer | |
|---|---|---|
| 1 | 4 | |
| 2,433 | 804 | |
| 1.5% | 3.5% | |
| 0.0 | 0.0 | |
| 11 months ago | almost 3 years ago | |
| Jupyter Notebook | Python | |
| MIT License | MIT License |
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.
benchmarking-gnns
Posts with mentions or reviews of benchmarking-gnns.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-27.
-
[D] Laplacian positional encodings
Code for https://arxiv.org/abs/2003.00982 found: https://github.com/graphdeeplearning/benchmarking-gnns
graphtransformer
Posts with mentions or reviews of graphtransformer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-27.
-
[D] Laplacian positional encodings
Code for https://arxiv.org/abs/2012.09699 found: https://github.com/graphdeeplearning/graphtransformer
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Resources for graphs and graph based neural networks.
Hi everyone. I am Harshit. I am looking for some resources for GNN's. I am beginner so will you please help me find some resources for the same? I am working on Transformer based Graph networks. (Here)[https://github.com/graphdeeplearning/graphtransformer] is the link of the paper's implementation on which I am working.
What are some alternatives?
When comparing benchmarking-gnns and graphtransformer you can also consider the following projects:
graphein - Protein Graph Library
performer-pytorch - An implementation of Performer, a linear attention-based transformer, in Pytorch
spektral - Graph Neural Networks with Keras and Tensorflow 2.
gnn-lspe - Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
GraphGPS - Recipe for a General, Powerful, Scalable Graph Transformer
LFattNet - Attention-based View Selection Networks for Light-field Disparity Estimation