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Search results for machine learning quantum chemistry
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quantum-chemistry
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18 search results found
Pennylane
⭐
2,170
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Schnetpack
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688
SchNetPack - Deep Neural Networks for Atomistic Systems
Computationalphysics2
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143
Advanced course in Computational Physics, see texbook at http://compphysics.github.io/ComputationalPhysics2 with an emphasis on computational quantum mechanics, machine learning and quantum computing.
Sgdml
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124
sGDML - Reference implementation of the Symmetric Gradient Domain Machine Learning model
Nabladft
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117
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
Delfta
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82
Δ-QML for medicinal chemistry
Alchemy
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69
Awesome Structural Bioinformatics
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54
Structural Bioinformatics is awesome. Throw your textbook in the garbage, light the garbage can on fire, and blend the ashes into your cold brew almond milk latte and read this.
Dtnn
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52
Deep Tensor Neural Network
Kallisto
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50
Efficiently calculate 3D-features for quantitative structure-activity relationship approaches.
Soaplite
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31
Fast lightweight SOAP implementation for machine learning in quantum chemistry and materials physics.
Book_about_quadratization
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16
Open collaborative book on quadratization in discrete optimization and quantum mechanics.
Aqml
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14
Amons-based quantum machine learning for quantum chemistry
Swan
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13
Statistical models to predict new materials
Hotpot
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11
A python package designed to communicate among various chemical and materials calculational tools
Qchem
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10
An exploration of the state of the art in the application of data science to quantum chemistry.
Mbgdml
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8
Create, use, and analyze machine learning potentials within the many-body expansion framework.
Quantumpdb
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7
Workflow for generate a database of proteins with quantum properties
Pysirc
⭐
5
Simple web application for prediction of reaction rate constant through machine learning models using molecular fingerprints.
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