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Deep learning for molecules and materials book
DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules…
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A toolkit for developing and comparing reinforcement learning algorithms.
End-To-End Molecular Dynamics (MD) Engine using PyTorch
Python library written in C++ for calculation of local atomic structural environment
Examples for pyscal local atomic environment calculator
an automatic reaction network generator for reactive molecular dynamics simulation
Molecular dynamics and Monte Carlo soft matter simulation on GPUs.
FAIR Chemistry's library of machine learning methods for chemistry
A code to generate atomic structure with symmetry
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
This is post-analysis tools for TPS module in USPEX
Elyra extends JupyterLab with an AI centric approach.
Robust representation of semantically constrained graphs, in particular for molecules in chemistry
🔺 Ternary plotting library for python with matplotlib
Extensible, Efficient Quantum Algorithm Design for Humans.
Automated Machine Learning with scikit-learn
ASAP is a package that can quickly analyze and visualize datasets of crystal or molecular structures.
A Python package for manipulating atomistic data of software in computational science
Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
A Python package to compute bond orientational order parameters as defined by Steinhardt, Physical Review B (1983)