Statistics for topic materials-science
RepositoryStats tracks 592,850 Github repositories, of these 92 are tagged with the materials-science topic. The most common primary language for repositories using this topic is Python (50). Other languages include: Jupyter Notebook (17)
Stargazers over time for topic materials-science
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Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT
3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT
A Bayesian global optimization package for material design ｜ Adaptive Learning | Active Learning
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
A deep learning package for many-body potential energy representation and molecular dynamics
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...
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
3D model exchange format with physical material properties for virtual development, test and validation of automated driving.
SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
A deep learning package for many-body potential energy representation and molecular dynamics
NequIP is a code for building E(3)-equivariant interatomic potentials
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Home for GSAS-II: crystallographic and diffraction-based structural characterization of materials
SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
Home for GSAS-II: crystallographic and diffraction-based structural characterization of materials
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
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
NequIP is a code for building E(3)-equivariant interatomic potentials
Home for GSAS-II: crystallographic and diffraction-based structural characterization of materials
Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
SLICES: An Invertible, Invariant, and String-based Crystal Representation [2023, Nature Communications] MatterGPT