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Matthew Ragoza et al.
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Felix A. Faber et al.
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The atomic simulation environment-a Python library for working with atoms
Ask Hjorth Larsen et al.
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J. S. Smith et al.
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Quantum-chemical insights from deep tensor neural networks
Kristof T. Schuett et al.
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Olexandr Isayev et al.
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Turki Turki et al.
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ANI-1, A data set of 20 million calculated off-equilibrium conformations for organic molecules
Justin S. Smith et al.
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Albert P. Bartok et al.
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Aldo Glielmo et al.
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Jan Hermann et al.
CHEMICAL REVIEWS (2017)
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Sarah Rauscher et al.
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Raghunathan Ramakrishnan et al.
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Zhenwei Li et al.
PHYSICAL REVIEW LETTERS (2015)
Machine learning: Trends, perspectives, and prospects
M. I. Jordan et al.
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Yolanda Gil et al.
SCIENCE (2014)
Inferring multi-target QSAR models with taxonomy-based multi-task learning
Lars Rosenbaum et al.
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Ron O. Dror et al.
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Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Matthias Rupp et al.
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The Protein-Folding Problem, 50 Years On
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The ORCA program system
Frank Neese
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W4-11: A high-confidence benchmark dataset for computational thermochemistry derived from first-principles W4 data
Amir Karton et al.
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Assessment of the Performance of DFT and DFT-D Methods for Describing Distance Dependence of Hydrogen-Bonded Interactions
Kanchana S. Thanthiriwatte et al.
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Jan Rezac et al.
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Generalized Gradient Approximation That Recovers the Second-Order Density-Gradient Expansion with Optimized Across-the-Board Performance
Roberto Peverati et al.
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Sijie Luo et al.
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Density functional theory with London dispersion corrections
Stefan Grimme
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Sinno Jialin Pan et al.
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Jeng-Da Chai et al.
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A simple and efficient CCSD(T)-F12 approximation
Thomas B. Adler et al.
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Coupled-cluster theory in quantum chemistry
Rodney J. Bartlett et al.
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Mechanical properties of nanocrystalline materials
MA Meyers et al.
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Sources of error in electronic structure calculations on small chemical systems
D Feller et al.
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Toward true DNA base-stacking energies: MP2, CCSD(T), and complete basis set calculations
P Hobza et al.
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