CrabNet
Predict materials properties using only the composition information! (by anthony-wang)
mat2vec
Supplementary Materials for Tshitoyan et al. "Unsupervised word embeddings capture latent knowledge from materials science literature", Nature (2019). (by materialsintelligence)
CrabNet | mat2vec | |
---|---|---|
1 | 1 | |
81 | 607 | |
- | 0.3% | |
3.7 | 3.1 | |
about 1 year ago | about 1 year 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.
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
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.
mat2vec
Posts with mentions or reviews of mat2vec.
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
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.
What are some alternatives?
When comparing CrabNet and mat2vec you can also consider the following projects:
Invariant-Attention - An implementation of Invariant Point Attention from Alphafold 2
query-selector - LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)
hummingbird - Hummingbird compiles trained ML models into tensor computation for faster inference.
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.