deep_gcns_torch VS GraphMixerNetworks

Compare deep_gcns_torch vs GraphMixerNetworks and see what are their differences.

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deep_gcns_torch GraphMixerNetworks
1 2
1,118 15
- -
0.0 4.4
almost 2 years ago 5 months ago
Python 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.

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.

GraphMixerNetworks

Posts with mentions or reviews of GraphMixerNetworks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-03.

What are some alternatives?

When comparing deep_gcns_torch and GraphMixerNetworks you can also consider the following projects:

pytorch_geometric - Graph Neural Network Library for PyTorch

chemicalx - A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)

dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.

bottleneck - Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

graphlearn-for-pytorch - A GPU-accelerated graph learning library for PyTorch, facilitating the scaling of GNN training and inference.

Ringer-Client - Ringer is a new messaging app for windows. Its currently in beta but lets work together to make it better. The code here is snapshot code so it might not work as intended. To get the latest stable build pls download the installer.

do-you-even-need-attention - Is the attention layer even necessary? (https://arxiv.org/abs/2105.02723)

Bi-Real-net - Bi-Real Net: Enhancing the Performance of 1-bit CNNs With Improved Representational Capability and Advanced Training Algorithm. In ECCV 2018 and IJCV

nasa_impacts - Plotly visualizations of NASA's IMPACTS snow storm study program