CrabNet
Invariant-Attention
| CrabNet | Invariant-Attention | |
|---|---|---|
| 1 | 1 | |
| 81 | 6 | |
| - | - | |
| 3.7 | 10.0 | |
| about 1 year ago | over 1 year ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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CrabNet
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Artificial intelligence can revolutionise science
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.
Invariant-Attention
What are some alternatives?
query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
af2complex - Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.
GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
mat2vec - Supplementary Materials for Tshitoyan et al. "Unsupervised word embeddings capture latent knowledge from materials science literature", Nature (2019).
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.