Statistics for topic materials-science
RepositoryStats tracks 518,325 Github repositories, of these 78 are tagged with the materials-science topic. The most common primary language for repositories using this topic is Python (42). Other languages include: Jupyter Notebook (15)
Stargazers over time for topic materials-science
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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 Pro...
A deep learning package for many-body potential energy representation and molecular dynamics
atomate2 is a library of computational materials science workflows
atomate2 is a library of computational materials science workflows
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 Pro...
A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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 Pro...
A deep learning package for many-body potential energy representation and molecular dynamics
Development of the Failure Criteria for Composites using ABAQUS Subroutines (UMAT/VUMAT)
Development of the Failure Criteria for Composites using ABAQUS Subroutines (UMAT/VUMAT)
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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 Pro...
A deep learning package for many-body potential energy representation and molecular dynamics
DScribe is a python package for creating machine learning descriptors for atomistic systems.
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
SLICES: An Invertible, Invariant, and String-based Crystal Representation (Text2Crystal)
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
Online resource for a practical course in machine learning for materials research at Imperial College London (MATE70026)
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
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 Pro...
A deep learning package for many-body potential energy representation and molecular dynamics
NequIP is a code for building E(3)-equivariant interatomic potentials
[ICLR'24] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
A Bayesian global optimization package for material design ｜ Adaptive Learning | Active Learning
[ICLR'23 Spotlight] Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs