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检索条件"机构=Program in Applied and Computational Mathematics"
1033 条 记 录,以下是571-580 订阅
排序:
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
arXiv
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arXiv 2019年
作者: Wang, Haidi Chen, Weijie Zeng, Jinzhe Zhang, Linfeng Wang, Han Zhang, Yuzhi Weinan, E. Yuanpei College of Peking University Beijing100871 China School of Electronic Science and Applied Physics Hefei University of Technology Hefei230601 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China School of Chemistry and Molecular Engineering East China Normal University Shanghai200062 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China Beijing Institute of Big Data Research Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Beijing Institute of Big Data Research Beijing100871 China
In recent years, promising deep learning based interatomic potential energy surface (PES) models have been proposed that can potentially allow us to perform molecular dynamics simulations for large scale systems with ... 详细信息
来源: 评论
Dynamic Measure of Hyperuniformity and Nonhyperuniformity in Heterogeneous Media via the Diffusion Spreadability
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Physical Review applied 2022年 第3期17卷 034022-034022页
作者: Haina Wang Salvatore Torquato Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Chemistry Department of Physics Princeton Center for Theoretical Science Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA
Time-dependent interphase diffusion processes in multiphase heterogeneous media are ubiquitous phenomena in physics, chemistry and biology. Examples of heterogeneous media include composites, geological media, gels, f... 详细信息
来源: 评论
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning...
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IEEE Conference on Decision and Control
作者: Thomas Beckers Jacob Seidman Paris Perdikaris George J. Pappas Department of Electrical and Systems Engineering University of Pennsylvania Philadelphia PA USA graduate program in Applied Mathematics and Computational Science University of Pennsylvania Philadelphia PA USA Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Philadelphia PA USA
Data-driven approaches achieve remarkable results for the modeling of complex dynamics based on collected data. However, these models often neglect basic physical principles which determine the behavior of any real-wo... 详细信息
来源: 评论
computational Methods for Single-Particle Cryo-EM
arXiv
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arXiv 2020年
作者: Singer, Amit Sigworth, Fred J. Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Departments of Cellular and Molecular Physiology Biomedical Engineering and Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States
Single-particle electron cryomicroscopy (cryo-EM) is an increasingly popular technique for elucidating the three-dimensional structure of proteins and other biologically significant complexes at near-atomic resolution... 详细信息
来源: 评论
Blind phaseless short-time fourier transform recovery
arXiv
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arXiv 2018年
作者: Bendory, Tamir Edidin, Dan Eldar, Yonina C. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Department of Mathematics University of Missouri ColumbiaMO United States Andrew and Erna Viterbi Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa Israel
The problem of recovering a pair of signals from their blind phaseless short-time Fourier transform measurements arises in several important phase retrieval applications, including ptychography and ultra-short pulse c... 详细信息
来源: 评论
On signal reconstruction from frog measurements
arXiv
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arXiv 2017年
作者: Bendory, Tamir Edidin, Dan Eldar, Yonina C. Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Department of Mathematics University of Missouri ColumbiaMO United States The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion – Israel Institute of Technology Haifa Israel
Phase retrieval refers to recovering a signal from its Fourier magnitude. This problem arises naturally in many scientific applications, such as ultra-short laser pulse characterization and diffraction imaging. Unfort... 详细信息
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Multifunctional hyperuniform cellular networks: Optimality, anisotropy and disorder
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Multifunctional Materials 2018年 第1期1卷
作者: Torquato, S. Chen, D. Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Princeton University PrincetonNJ08544 United States
Disordered hyperuniform heterogeneousmaterials are new, exotic amorphous states of matter that behave like crystals in themanner in which they suppress volume-fraction fluctuations at large length scales, and yet are ... 详细信息
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Deep density: Circumventing the kohn-sham equations via symmetry preserving neural networks
arXiv
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arXiv 2019年
作者: Zepeda-Núñez, Leonardo Chen, Yixiao Zhang, Jiefu Zhang, Linfeng Jia, Weile Lin, Lin Department of Mathematics University of Wisconsin-Madison MadisonWI53706 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Mathematics University of California Berkeley BerkeleyCA94720 United States Department of Mathematics University of California Berkeley Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States
The recently developed Deep Potential [Phys. Rev. Lett. 120, 143001, 2018] is a powerful method to represent general inter-atomic potentials using deep neural networks. The success of Deep Potential rests on the prope... 详细信息
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First-principles study of the interfacial adhesion between SiO2 and MoSi2
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Physical Review B 2005年 第16期72卷 165410-165410页
作者: D. E. Jiang Emily A. Carter Department of Chemistry and Biochemistry Box 951569 University of California Los Angeles California 90095-1569 USA Department of Mechanical and Aerospace Engineering and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544-5263 USA
Upon oxidation, a silica scale forms on MoSi2, a potential high-temperature coating material for metals. This silica scale protects MoSi2 against high-temperature corrosive gases or liquids. We use periodic density fu...
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Neural Canonical Transformation with Symplectic Flows
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Physical Review X 2020年 第2期10卷 021020-021020页
作者: Shuo-Hui Li Chen-Xiao Dong Linfeng Zhang Lei Wang Institute of Physics Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA Songshan Lake Materials Laboratory Dongguan Guangdong 523808 China
Canonical transformation plays a fundamental role in simplifying and solving classical Hamiltonian systems. Intriguingly, it has a natural correspondence to normalizing flows with a symplectic constraint. Building on ... 详细信息
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