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Solving many-electron Schrödinger equation using deep neural networks

Journal of computational physics, 2019-12, Vol.399, p.108929, Article 108929

2019

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Phase Diagram of a Deep Potential Water Model

Physical review letters, 2021-06, Vol.126 (23), p.1-236001, Article 236001

2021

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DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

Computer physics communications, 2020-08, Vol.253 (C), p.107206, Article 107206

2020

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DeePCG: Constructing coarse-grained models via deep neural networks

The Journal of chemical physics, 2018-07, Vol.149 (3), p.034101-034101

2018

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Energy management in a microgrid with distributed energy resources

Energy conversion and management, 2014-02, Vol.78, p.297-305

2014

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Accurate Deep Potential model for the Al–Cu–Mg alloy in the full concentration space

Chinese physics B, 2021-05, Vol.30 (5), p.50706-21

2021

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Raman spectrum and polarizability of liquid water from deep neural networks

Physical chemistry chemical physics : PCCP, 2020-05, Vol.22 (19), p.1592-162

2020

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Signatures of a liquid–liquid transition in an ab initio deep neural network model for water

Proceedings of the National Academy of Sciences - PNAS, 2020-10, Vol.117 (42), p.26040-26046

2020

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Free energy of proton transfer at the water–TiO2 interface from ab initio deep potential molecular dynamics

Chemical science (Cambridge), 2020-03, Vol.11 (9), p.2335-2341

2020

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The performance of a grid-tied microgrid with hydrogen storage and a hydrogen fuel cell stack

Energy conversion and management, 2014-11, Vol.87, p.421-427

2014

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Deep learning inter-atomic potential model for accurate irradiation damage simulations

Applied physics letters, 2019-06, Vol.114 (24)

2019

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Multi-UAV Data Collection and Path Planning Method for Large-Scale Terminal Access

Sensors (Basel, Switzerland), 2023-10, Vol.23 (20), p.8601

2023

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Deep neural network for the dielectric response of insulators

Physical review. B, 2020-07, Vol.102 (4), p.1, Article 041121

2020

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Viscosity in water from first-principles and deep-neural-network simulations

npj computational materials, 2022-07, Vol.8 (1), p.1-10, Article 139

2022

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Isotope effects in liquid water via deep potential molecular dynamics

Molecular physics, 2019-11, Vol.117 (22), p.3269-3281

2019

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One-pot synthesized NiFe2O4/CeO2 composite catalyst for efficient degradation of methylene blue via photocatalysis under visible light

Catalysis communications, 2023-12, Vol.185, p.106814, Article 106814

2023

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Isotope effects in molecular structures and electronic properties of liquid water via deep potential molecular dynamics based on the SCAN functional

Physical review. B, 2020-12, Vol.102 (21), p.1, Article 214113

2020

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Neural Canonical Transformation with Symplectic Flows

Physical review. X, 2020-04, Vol.10 (2), p.021020, Article 021020

2020

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Crystal Structure Prediction of Binary Alloys via Deep Potential

Frontiers in chemistry, 2020-11, Vol.8, p.589795-589795

2020

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m^$ of two-dimensional electron gas: A neural canonical transformation study

SciPost physics, 2023-06, Vol.14 (6), p.154, Article 154

2023

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Specialising neural network potentials for accurate properties and application to the mechanical response of titanium

npj computational materials, 2021-12, Vol.7 (1), p.1-11, Article 206

2021

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A Joint Graph-Based Approach for Simultaneous Underwater Localization and Mapping for AUV Navigation Fusing Bathymetric and Magnetic-Beacon-Observation Data

Journal of marine science and engineering, 2024-06, Vol.12 (6), p.954

2024

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Docosahexaenoic acid supresses breast cancer cell proliferation and migration by promoting the expression of miR-99a and targeting mTOR signaling

Arabian journal of chemistry, 2021-08, Vol.14 (8), p.103298, Article 103298

2021

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Prediction of Marine Pycnocline Based on Kernel Support Vector Machine and Convex Optimization Technology

Sensors (Basel, Switzerland), 2019-03, Vol.19 (7), p.1562

2019

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DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

Computer physics communications, 2018-07, Vol.228 (C), p.178-184

2018

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Solving many-electron Schrödinger equation using deep neural networks

Phase Diagram of a Deep Potential Water Model

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

DeePCG: Constructing coarse-grained models via deep neural networks

Energy management in a microgrid with distributed energy resources

Accurate Deep Potential model for the Al–Cu–Mg alloy in the full concentration space

Raman spectrum and polarizability of liquid water from deep neural networks

Signatures of a liquid–liquid transition in an ab initio deep neural network model for water

Free energy of proton transfer at the water–TiO2 interface from ab initio deep potential molecular dynamics

The performance of a grid-tied microgrid with hydrogen storage and a hydrogen fuel cell stack

Deep learning inter-atomic potential model for accurate irradiation damage simulations

Multi-UAV Data Collection and Path Planning Method for Large-Scale Terminal Access

Deep neural network for the dielectric response of insulators

Viscosity in water from first-principles and deep-neural-network simulations

Isotope effects in liquid water via deep potential molecular dynamics

One-pot synthesized NiFe2O4/CeO2 composite catalyst for efficient degradation of methylene blue via photocatalysis under visible light

Isotope effects in molecular structures and electronic properties of liquid water via deep potential molecular dynamics based on the SCAN functional

Neural Canonical Transformation with Symplectic Flows

Crystal Structure Prediction of Binary Alloys via Deep Potential

m^$ of two-dimensional electron gas: A neural canonical transformation study

Specialising neural network potentials for accurate properties and application to the mechanical response of titanium

A Joint Graph-Based Approach for Simultaneous Underwater Localization and Mapping for AUV Navigation Fusing Bathymetric and Magnetic-Beacon-Observation Data

Docosahexaenoic acid supresses breast cancer cell proliferation and migration by promoting the expression of miR-99a and targeting mTOR signaling

Prediction of Marine Pycnocline Based on Kernel Support Vector Machine and Convex Optimization Technology

DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

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