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Quantum deep field: data-driven wave function, electron density
  generation, and atomization energy prediction and extrapolation with machine
  learning

Quantum deep field: data-driven wave function, electron density generation, and atomization energy prediction and extrapolation with machine learning

Physical Review Letters (PRL), 2020
16 November 2020
Masashi Tsubaki
T. Mizoguchi
ArXiv (abs)PDFHTMLGithub (219★)

Papers citing "Quantum deep field: data-driven wave function, electron density generation, and atomization energy prediction and extrapolation with machine learning"

9 / 9 papers shown
Machine Learning Time Propagators for Time-Dependent Density Functional Theory Simulations
Machine Learning Time Propagators for Time-Dependent Density Functional Theory Simulations
Karan Shah
A. Cangi
AI4CE
252
2
0
22 Aug 2025
A Tutorial on the Use of Physics-Informed Neural Networks to Compute the
  Spectrum of Quantum Systems
A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systems
Lorenzo Brevi
Antonio Mandarino
Enrico Prati
201
10
0
30 Jul 2024
A cyclical route linking fundamental mechanism and AI algorithm: An
  example from tuning Poisson's ratio in amorphous networks
A cyclical route linking fundamental mechanism and AI algorithm: An example from tuning Poisson's ratio in amorphous networks
Changliang Zhu
Chenchao Fang
Zhipeng Jin
Baowen Li
Xiangying Shen
Lei Xu
324
9
0
06 Dec 2023
Equivariant Neural Operator Learning with Graphon Convolution
Equivariant Neural Operator Learning with Graphon Convolution
Chaoran Cheng
Jian-wei Peng
210
7
0
17 Nov 2023
Descriptors for Machine Learning Model of Generalized Force Field in
  Condensed Matter Systems
Descriptors for Machine Learning Model of Generalized Force Field in Condensed Matter Systems
Puhan Zhang
Sheng Zhang
Gia-Wei Chern
AI4CE
240
16
0
03 Jan 2022
Machine learning nonequilibrium electron forces for adiabatic spin
  dynamics
Machine learning nonequilibrium electron forces for adiabatic spin dynamicsnpj Computational Materials (npj Comput Mater), 2021
Puhan Zhang
Gia-Wei Chern
155
25
0
22 Dec 2021
Equivariant graph neural networks for fast electron density estimation
  of molecules, liquids, and solids
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids
Peter Bjørn Jørgensen
Arghya Bhowmik
254
61
0
01 Dec 2021
Audacity of huge: overcoming challenges of data scarcity and data
  quality for machine learning in computational materials discovery
Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discoveryCurrent Opinion in Chemical Engineering (Curr Opin Chem Eng), 2021
Aditya Nandy
Chenru Duan
Heather J. Kulik
AI4CE
280
69
0
02 Nov 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave
  Functions
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave FunctionsInternational Conference on Learning Representations (ICLR), 2021
Nicholas Gao
Stephan Günnemann
260
52
0
11 Oct 2021
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