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Papers: 10.1039/d0sc01101k

https://doi.org/10.1039/d0sc01101k

Autonomous intelligent agents for accelerated materials discovery

Cited by: 46
Author(s): Joseph H. Montoya, Kirsten T. Winther, Raul A. Flores, Thomas Bligaard, Jens Strabo Hummelshøj, Muratahan Aykol
Published: over 6 years ago

Software Mentions 8

cran: tensorflow
R Interface to 'TensorFlow'
Papers that mentioned: 71
Very Likely Science (100)
pypi: gpflow
Gaussian process methods in TensorFlow
Papers that mentioned: 1
Very Likely Science (80)
pypi: matminer
matminer is a library that contains tools for data mining in Materials Science
Papers that mentioned: 4
Very Likely Science (100)
pypi: protosearch
Software for enumerating crystal structure prototypes to by used for active learning exploration with DFT and machine learning.
Papers that mentioned: 1
Very Likely Science (90)
pypi: pymatgen
Python Materials Genomics is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project (https://materialsproject.org).
Papers that mentioned: 47
Very Likely Science (90)
pypi: qmpy
Suite of computational materials science tools
Papers that mentioned: 4
Very Likely Science (75)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)
pypi: tensorflow
TensorFlow is an open source machine learning framework for everyone.
Papers that mentioned: 71
Very Likely Science (90)