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Работы, на которые ссылается эта работа
Работ: 75
Работа: GrapheNet: a deep learning framework for predicting the physical and electronic properties of nanographenes using images
VMD: Visual molecular dynamics
William Humphrey, Andrew Dalke, Klaus Schulten
Статья1996Цитирований: 77ABIDeep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren +1
Статья2016Цитирований: 61ABIDFTB+, a software package for efficient approximate density functional theory based atomistic simulations
B. Hourahine, Bálint Aradi, Volker Blüm +36
Статья2020Цитирований: 14ABI<i>Ab‐initio</i>simulations of materials using VASP: Density‐functional theory and beyond
Статья2008Цитирований: 13ABIGoing deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
Статья2015Цитирований: 11ABIUMAP: Uniform Manifold Approximation and Projection
Leland McInnes, John Healy, Nathaniel Saul +1
Статья2018Цитирований: 3ABIGeneralized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
Jörg Behler, Michele Parrinello
Статья2007Цитирований: 2ABIFast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
Matthias Rupp, Alexandre Tkatchenko, Klaus‐Robert Müller +1
Статья2012Цитирований: 2ABI