sgas
SGAS: Sequential Greedy Architecture Search (CVPR'2020) https://www.deepgcns.org/auto/sgas (by lightaime)
DeepInteract
A geometric deep learning pipeline for predicting protein interface contacts. (ICLR 2022) (by BioinfoMachineLearning)
| sgas | DeepInteract | |
|---|---|---|
| 3 | 1 | |
| 160 | 53 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | almost 2 years ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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.
sgas
Posts with mentions or reviews of sgas.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-04.
DeepInteract
Posts with mentions or reviews of DeepInteract.
We have used some of these posts to build our list of alternatives
and similar projects.
What are some alternatives?
When comparing sgas and DeepInteract you can also consider the following projects:
pytorch_geometric - Graph Neural Network Library for PyTorch
EquiBind - EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.