v1v2 (latest)

Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics

30 July 2017

Papers citing "Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics"

50 / 125 papers shown

Title
Graph Neural Networks Accelerated Molecular Dynamics Zijie Li Kazem Meidani Prakarsh Yadav A. Farimani GNN AI4CE 72 60 0 06 Dec 2021
Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks Tian Zheng Weihao Gao Chong-Jun Wang AI4CE 68 4 0 30 Nov 2021
Deep Molecular Representation Learning via Fusing Physical and Chemical Information Shuwen Yang Ziyao Li Guojie Song Lingsheng Cai AI4CE 102 31 0 28 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 63 98 0 02 Nov 2021
Geometric Transformer for End-to-End Molecule Properties Prediction Yoni Choukroun Lior Wolf AI4CE ViT 78 16 0 26 Oct 2021
An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji Yiping Lu Yiliang Zhang Zhun Deng Weijie J. Su 212 87 0 06 Oct 2021
Complex Spin Hamiltonian Represented by Artificial Neural Network Hongyu Yu Changsong Xu Feng Lou L. Bellaiche Zhenpeng Hu X. Gong H. Xiang 73 15 0 02 Oct 2021
Fast and Sample-Efficient Interatomic Neural Network Potentials for Molecules and Materials Based on Gaussian Moments Viktor Zaverkin David Holzmüller Ingo Steinwart Johannes Kastner 72 21 0 20 Sep 2021
Heterogeneous relational message passing networks for molecular dynamics simulations Zun Wang Chong Wang Sibo Zhao Yong Xu Shaogang Hao Chang-Yu Hsieh B. Gu W. Duan 42 26 0 02 Sep 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 125 69 0 02 Jul 2021
On the Representation of Solutions to Elliptic PDEs in Barron Spaces Ziang Chen Jianfeng Lu Yulong Lu 83 29 0 14 Jun 2021
Learning Full Configuration Interaction Electron Correlations with Deep Learning H. Corzo Arijit Sehanobish Onur Kara 39 2 0 08 Jun 2021
Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry Zhuoran Qiao Anders S. Christensen Matthew Welborn F. Manby Anima Anandkumar Thomas F. Miller 134 74 0 31 May 2021
Arrested phase separation in double-exchange models: machine-learning enabled large-scale simulation Puhan Zhang Gia-Wei Chern 20 5 0 18 May 2021
BubbleNet: Inferring micro-bubble dynamics with semi-physics-informed deep learning Hanfeng Zhai Quan Zhou G. Hu PINN AI4CE 65 16 0 15 May 2021
Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure Juntao Huang Yingda Cheng Andrew J. Christlieb L. Roberts AI4CE 60 31 0 12 May 2021
Learning Gradient Fields for Molecular Conformation Generation Chence Shi Shitong Luo Minkai Xu Jian Tang DiffM AI4CE 109 216 0 09 May 2021
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 236 255 0 01 May 2021
Frame-independent vector-cloud neural network for nonlocal constitutive modeling on arbitrary grids Xueqing Zhou Jiequn Han Heng Xiao 82 31 0 11 Mar 2021
Error Estimates for the Deep Ritz Method with Boundary Penalty Johannes Müller Marius Zeinhofer 93 17 0 01 Mar 2021
A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space Kuo Gai Shihua Zhang 103 8 0 18 Feb 2021
A Universal Framework for Featurization of Atomistic Systems Xiangyun Lei A. Medford AI4CE 89 19 0 04 Feb 2021
Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks Yaoyu Zhang Yaoyu Zhang Zheng Ma Zhi-Qin John Xu 62 21 0 30 Jan 2021
Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks Daniel Schwalbe-Koda Aik Rui Tan Rafael Gómez-Bombarelli AAML 98 63 0 27 Jan 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 324 1,340 0 08 Jan 2021
Symmetry-adapted graph neural networks for constructing molecular dynamics force fields Zun Wang Chong Wang Sibo Zhao Shiqiao Du Yong Xu B. Gu W. Duan AI4CE 108 14 0 08 Jan 2021
Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks Matthew T.C. Li L. Demanet Leonardo Zepeda-Núnez 84 9 0 24 Nov 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 145 940 0 14 Oct 2020
Efficient Long-Range Convolutions for Point Clouds Yifan Peng Lin Lin Lexing Ying Leonardo Zepeda-Núnez 3DPC 47 8 0 11 Oct 2020
Accelerating Finite-temperature Kohn-Sham Density Functional Theory with Deep Neural Networks J. Ellis Lenz Fiedler G. Popoola N. Modine J. A. Stephens A. Thompson A. Cangi S. Rajamanickam AI4CE 58 40 0 10 Oct 2020
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 63 16 0 28 Sep 2020
Machine Learning and Computational Mathematics Weinan E PINN AI4CE 88 62 0 23 Sep 2020
Multi-scale approach for the prediction of atomic scale properties Andrea Grisafi Jigyasa Nigam Michele Ceriotti 43 31 0 27 Aug 2020
Bayesian Force Fields from Active Learning for Simulation of Inter-Dimensional Transformation of Stanene Yu Xie Jonathan Vandermause Lixin Sun Andrea Cepellotti Boris Kozinsky 24 3 0 26 Aug 2020
Machine Learning in Nano-Scale Biomedical Engineering Alexandros-Apostolos A. Boulogeorgos Stylianos E. Trevlakis Sotiris A. Tegos V. Papanikolaou G. Karagiannidis AI4CE 41 30 0 05 Aug 2020
DeePKS: a comprehensive data-driven approach towards chemically accurate density functional theory Yixiao Chen Linfeng Zhang Han Wang E. Weinan 76 73 0 01 Aug 2020
Coarse Graining Molecular Dynamics with Graph Neural Networks B. Husic N. Charron Dominik Lemm Jiang Wang Adria Pérez ... Yaoyi Chen Simon Olsson Gianni De Fabritiis Frank Noé C. Clementi AI4CE 125 162 0 22 Jul 2020
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 89 161 0 16 Jul 2020
OrbNet: Deep Learning for Quantum Chemistry Using Symmetry-Adapted Atomic-Orbital Features Zhuoran Qiao Matthew Welborn Anima Anandkumar F. Manby Thomas F. Miller AI4CE 91 218 0 15 Jul 2020
Deep Learning for UV Absorption Spectra with SchNarc: First Steps Towards Transferability in Chemical Compound Space Julia Westermayr P. Marquetand 93 53 0 15 Jul 2020
Machine learning for electronically excited states of molecules Julia Westermayr P. Marquetand 71 266 0 10 Jul 2020
Geometric Prediction: Moving Beyond Scalars Raphael J. L. Townshend Brent Townshend Stephan Eismann R. Dror 79 7 0 25 Jun 2020
Machine learning dynamics of phase separation in correlated electron magnets Puhan Zhang P. Saha Gia-Wei Chern 31 16 0 07 Jun 2020
Integrating Machine Learning with Physics-Based Modeling E. Weinan Jiequn Han Linfeng Zhang PINN AI4CE 68 24 0 04 Jun 2020
Wavelet Scattering Networks for Atomistic Systems with Extrapolation of Material Properties Paul Sinz M. Swift Xavier Brumwell Jialin Liu K. Kim Y. Qi M. Hirn 55 12 0 01 Jun 2020
Machine learning and excited-state molecular dynamics Julia Westermayr P. Marquetand AI4CE 66 56 0 28 May 2020
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach Jiang Wang Stefan Chmiela K. Müller Frank Noè C. Clementi 138 46 0 04 May 2020
A Perspective on Deep Learning for Molecular Modeling and Simulations Jun Zhang Yao-Kun Lei Zhen Zhang Junhan Chang Maodong Li Xu Han Lijiang Yang Yue Yang Y. Gao AI4CE 116 8 0 25 Apr 2020
PFNN: A Penalty-Free Neural Network Method for Solving a Class of Second-Order Boundary-Value Problems on Complex Geometries H. Sheng Chao Yang 67 118 0 14 Apr 2020
Autonomous discovery in the chemical sciences part I: Progress Connor W. Coley Natalie S. Eyke K. Jensen 71 218 0 30 Mar 2020