CrabNet VS GAT

Compare CrabNet vs GAT and see what are their differences.

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CrabNet GAT
1 2
81 3,045
- -
3.7 0.0
about 1 year ago about 2 years 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.

CrabNet

Posts with mentions or reviews of CrabNet. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-09-15.
  • Artificial intelligence can revolutionise science
    2 projects | news.ycombinator.com | 15 Sep 2023
    I don't know. As for "literature-based discovery," this project/paper sounded like a pretty big deal when it came out a few years ago: https://github.com/materialsintelligence/mat2vec . And I see this thing came out more recently: https://github.com/anthony-wang/CrabNet .

    Of course not all fields lend themselves as well to this as does materials science.

GAT

Posts with mentions or reviews of GAT. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-09.

What are some alternatives?

When comparing CrabNet and GAT you can also consider the following projects:

Invariant-Attention - An implementation of Invariant Point Attention from Alphafold 2

pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

awesome-graph-classification - A collection of important graph embedding, classification and representation learning papers with implementations.

hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.

how_attentive_are_gats - Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

mat2vec - Supplementary Materials for Tshitoyan et al. "Unsupervised word embeddings capture latent knowledge from materials science literature", Nature (2019).

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

Perceiver - Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow

ViTGAN - A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.