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Quantum Chemistry in the Age of Machine Learning | The Journal of Physical Chemistry Letters
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials | Journal of Chemical Theory and Computation
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Neural Network Potential Energy Surfaces for Small Molecules and Reactions | Chemical Reviews
Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems | Journal of Chemical Theory and Computation
Neural network potentials for chemistry: concepts, applications and prospects - Digital Discovery (RSC Publishing) DOI:10.1039/D2DD00102K
Big-Data Science in Porous Materials: Materials Genomics and Machine Learning | Chemical Reviews
PotentialNet for Molecular Property Prediction | ACS Central Science
Machine Learning for Electronically Excited States of Molecules | Chemical Reviews
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Network-scale traffic prediction via knowledge transfer and regional MFD analysis - ScienceDirect
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials | Journal of Chemical Theory and Computation
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Machine Learning for Chemical Reactions | Chemical Reviews
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QSAR without borders - Chemical Society Reviews (RSC Publishing) DOI:10.1039/D0CS00098A
Machine‐learning‐based interatomic potentials for advanced manufacturing - Yu - 2021 - International Journal of Mechanical System Dynamics - Wiley Online Library
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Integrating Machine Learning in the Coarse-Grained Molecular Simulation of Polymers | The Journal of Physical Chemistry B