GNNPapers VS ABigSurvey

Compare GNNPapers vs ABigSurvey and see what are their differences.

GNNPapers

Must-read papers on graph neural networks (GNN) (by thunlp)

ABigSurvey

A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML). (by NiuTrans)
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GNNPapers ABigSurvey
1 1
15,548 1,951
0.6% 1.5%
0.0 3.8
5 months ago about 1 month ago
- 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.

GNNPapers

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

ABigSurvey

Posts with mentions or reviews of ABigSurvey. We have used some of these posts to build our list of alternatives and similar projects.
  • Becoming a ML/DL researcher
    1 project | /r/learnmachinelearning | 20 Feb 2021
    Find out a couple of survey papers (e.g., https://github.com/NiuTrans/ABigSurvey) and start reading them. Don't go into the details at first. Develop a broader picture - what is important, why is it important, is it worth applying ML to that topic, and most importantly if given that problem how would you approach it.

What are some alternatives?

When comparing GNNPapers and ABigSurvey you can also consider the following projects:

awesome-ml4co - Awesome machine learning for combinatorial optimization papers.

Awesome-Image-Inpainting - A curated list of image inpainting and video inpainting papers and resources

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

Machine-Learning-Tutorials - machine learning and deep learning tutorials, articles and other resources

start-machine-learning - A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2024 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

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

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

deep-finance - Datasets, papers and books on AI & Finance.