deep_gcns_torch
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org (by lightaime)
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks. (by dmlc)
| deep_gcns_torch | dgl | |
|---|---|---|
| 1 | 4 | |
| 1,118 | 13,050 | |
| - | 1.0% | |
| 0.0 | 9.9 | |
| almost 2 years ago | 5 days ago | |
| Python | Python | |
| 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.
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.
deep_gcns_torch
Posts with mentions or reviews of deep_gcns_torch.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-04.
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[R] Graph Convolutional Networks in Videos and 3D Point Clouds - Dr. Ali Thabet - Link to free zoom lecture by the author in comments
DeepGCNs: Can GCNs Go as Deep as CNNs? (ICCV 2019) Paper page: https://www.deepgcns.org/ Git: https://github.com/lightaime/deep_gcns_torch
dgl
Posts with mentions or reviews of dgl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-03.
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[P] We are building a curated list of open source tooling for data-centric AI workflows, looking for contributions.
For graph embeddings, there's quite a few. I'd recommend this one, but there's also this one (disclaimer: I'm the author) or this one, more of a DGL library.
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Detecting Out-of-Distribution Datapoints via Embeddings or Predictions
For trees/graphs, you’ll want a neural net that can take these as inputs for which I’m not sure a standard library exists. One recommendation is to checkout dgl: https://github.com/dmlc/dgl
- Beyond Message Passing: A Physics-Inspired Paradigm for Graph Neural Networks
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[D] Convenient libs to use for new research project at the intersection of GNN and RL.
The best pkg for GCN - https://github.com/dmlc/dgl
What are some alternatives?
When comparing deep_gcns_torch and dgl you can also consider the following projects:
pytorch_geometric - Graph Neural Network Library for PyTorch