GNNPapers VS awesome-ml4co

Compare GNNPapers vs awesome-ml4co and see what are their differences.

GNNPapers

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

awesome-ml4co

Awesome machine learning for combinatorial optimization papers. (by Thinklab-SJTU)
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GNNPapers awesome-ml4co
1 1
15,548 1,468
0.6% 2.9%
0.0 6.7
5 months ago 2 months ago
Python
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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.

awesome-ml4co

Posts with mentions or reviews of awesome-ml4co. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-04.

What are some alternatives?

When comparing GNNPapers and awesome-ml4co you can also consider the following projects:

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

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

ecole - Extensible Combinatorial Optimization Learning Environments

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

SeaPearl.jl - Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.

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

ml4vrp - Geometric Deep Learning Models for Vehicle Routing Problem

ABigSurvey - A collection of 1000+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML).

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