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Unsupervised learning of atomic environments from simple features
Wesley F. Reinhart
Materials Science and Engineering
Research output
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Contribution to journal
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Article
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peer-review
21
Scopus citations
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Dive into the research topics of 'Unsupervised learning of atomic environments from simple features'. Together they form a unique fingerprint.
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Keyphrases
Atomic Environment
100%
Body Features
25%
Bulk Material
25%
Chemical Species
25%
Classification Performance
25%
Collective Variables
25%
Colloidal Crystallization
25%
Crystal Lattice
25%
Ice Crystals
25%
Latent Space
25%
Low-dimensional Embedding
25%
Mesophases
50%
Microstructure
25%
Molecular Simulation
50%
Multiple Chemicals
25%
Neural Network
25%
Ordered Crystal
25%
Permutation Invariant
25%
Rotation Invariance
25%
Simple Features
100%
Simulation Context
25%
Simulation-based
25%
Supervised Classifier
25%
Three-body
25%
Unsupervised Learning
100%
Well-ordered
25%
Computer Science
Classification Performance
100%
Collective Variable
100%
Manifold Learning
100%
Neural Network
100%
Priori Knowledge
100%
Unsupervised Learning
100%
Chemical Engineering
Chemical Compound
100%
Unsupervised Learning
100%
Material Science
Crystal Lattice
50%
Molecular Simulation
100%