CrabNet VS data-resources-for-materials-science

Compare CrabNet vs data-resources-for-materials-science and see what are their differences.

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CrabNet data-resources-for-materials-science
1 3
96 302
- 6.3%
3.7 3.8
almost 2 years ago 29 days ago
Python
MIT License -
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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.

data-resources-for-materials-science

Posts with mentions or reviews of data-resources-for-materials-science. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing CrabNet and data-resources-for-materials-science you can also consider the following projects:

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

pymatgen - Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.

ProteinStructurePrediction - Protein structure prediction is the task of predicting the 3-dimensional structure (shape) of a protein given its amino acid sequence and any available supporting information. In this section, we will Install and inspect sidechainnet, a dataset with tools for predicting and inspecting protein structures, complete two simplified implementations of Attention based Networks for predicting protein angles from amino acid sequences, and visualize our predictions along the way.

Quantum_Espresso_Colab - This repository includes a notebook to run the open-source materials modeling package Quantum Espresso on Google Colab.

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

BestPractices - Things that you should (and should not) do in your Materials Informatics research.

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

material-design-icons - Material Design icons by Google (Material Symbols)

GAT - Graph Attention Networks (https://arxiv.org/abs/1710.10903)

MaterialDesign - ✒7000+ Material Design Icons from the Community

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

Perceiver - Implementation of Perceiver, General Perception with Iterative Attention

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