awesome-machine-learning-atomistic-simulation
github.com/m-k-s/awesome-machine-learning-atomistic-simulation ↗An overview of literature that discusses the use of machine learning for atomistic simulations
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Installation instructions →What's inside
Tools and Architectures
- 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Datae3nn Precursor
Weiler, Geiger, Welling, Boomsma, Cohen
- Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural NetworksMiscellaneous
Pfau, Spencer, de G. Matthews, Foulkes
- Accurate and scalable graph neural network force field and molecular dynamics with direct force architectureMiscellaneous
Park, Kornbluth, Vandermause, Wolverton, Kozinsky, Mailoa
- Accurate Molecular Dynamics Enabled by Efficient Physically-Constrained Machine Learning ApproachesSymmetric Gradient Domain Machine Learning (sGDML)
Chmiela, Sauceda, Tkatchenko, Muller
- A deep neural network for molecular wave functions in quasi-atomic minimal basis representationSchNet
Gastegger, McSloy, Luya, Schutt, Maurer
- A fast neural network approach for direct covariant forces prediction in complex multi-element extended systemsMiscellaneous
Mailoa, Kornbluth, Batzner, Samsonidze, Lam, Vandermause, Ablitt, Molinari, Kozinsky
Embeddings and Representations
- Accuracy and transferability of GAP models for tungstenGaussian Approximation Potentials (GAP)
Szlachta, Bartok, Csanyi
- A fingerprint based metric for measuring similarities of crystalline structuresMiscellaneous
Zhu, Amsler, Fuhrer, Schaefer, Faraji, Rostami, Ghasemi, Sadeghi, Grauzinyte, Wolverton, Goedecker
- A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transferAtom-Centered Symmetry Functions (ACSF)
Wai Ko, Finkler, Goedecker, Behler
- Alchemical and structural distribution based representation for universal quantum machine learningFCHL
Faber, Christensen, Huang, von Lilienfeld
- Amp: A modular approach to machine learning in atomistic simulationsAtom-Centered Symmetry Functions (ACSF)
Khorshidi, Peterson
- An assessment of the structural resolution of various fingerprints commonly used in machine learningMeta-literature
Karamad, Magar, Shi, Siahrostami, Gates, Farimani
Showing a sample of 140 resources. View the full list on GitHub →