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检索条件"机构=Department of Mathematics&Program in Applied and Computational Mathematics"
820 条 记 录,以下是421-430 订阅
排序:
Hyperuniform states of matter
arXiv
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arXiv 2018年
作者: Torquato, Salvatore 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
Hyperuniform states of matter are correlated systems that are characterized by an anomalous suppression of long-wavelength (i.e., large-length-scale) density fluctuations compared to those found in garden-variety diso... 详细信息
来源: 评论
Estimation in the group action channel
arXiv
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arXiv 2018年
作者: Abbe, Emmanuel Pereira, João M. Singer, Amit Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Electrical Engineering Department Princeton University PrincetonNJ United States Department of Mathematics Princeton University PrincetonNJ United States
MSC Codes 94A15, 62B10We analyze the problem of estimating a signal from multiple measurements on a group action channel that linearly transforms a signal by a random group action followed by a fixed projection and ad... 详细信息
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Communication-computation efficient gradient coding
arXiv
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arXiv 2018年
作者: Ye, Min Abbe, Emmanuel Department of Electrical Engineering Princeton University PrincetonNJ United States Program in Applied and Computational Mathematics Department of Electrical Engineering Princeton University School of Mathematics Institute for Advanced Study PrincetonNJ08544 United States
This paper develops coding techniques to reduce the running time of distributed learning tasks. It characterizes the fundamental tradeoff to compute gradients (and more generally vector summations) in terms of three p... 详细信息
来源: 评论
Plane-wave analysis of a hyperbolic system of equations with relaxation in Rd
arXiv
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arXiv 2018年
作者: de Hoop, Maarten V. Liu, Jian-Guo Markowich, Peter A. Ussembayev, Nail S. Department of Computational and Applied Mathematics Rice University HoustonTX77005 United States Department of Mathematics Department of Physics Duke University DurhamNC27708 United States Applied Mathematics and Computer Science Program CEMSE Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Faculty of Mathematics University of Vienna ViennaA-1090 Austria Applied Mathematics and Computer Science Program CEMSE Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia
We consider a multi-dimensional scalar wave equation with memory corresponding to the viscoelastic material described by a generalized Zener model. We deduce that this relaxation system is an example of a non-strictly... 详细信息
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Hard convex lens-shaped particles: Characterization of dense disordered packings
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Physical Review E 2019年 第6期100卷 062902-062902页
作者: Giorgio Cinacchi Salvatore Torquato Departamento de Física Teórica de la Materia Condensada Instituto de Física de la Materia Condensada (IFIMAC) Instituto de Ciencias de Materiales "Nicolás Cabrera" Universidad Autónoma de Madrid Ciudad Universitaria de Cantoblanco E-28049 Madrid Spain. Department of Chemistry and Department of Physics Institute for the Science and Technology of Materials Program for Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA.
Among the family of hard convex lens-shaped particles (lenses), the one with aspect ratio equal to 2/3 is “optimal” in the sense that the maximally random jammed (MRJ) packings of such lenses achieve the highest pac... 详细信息
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A Priori Estimates For Two-layer Neural Networks
arXiv
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arXiv 2018年
作者: Weinan, E. Ma, Chao Wu, Lei Department of Mathematics Princeton University United States Program in Applied and Computational Mathematics Princeton University United States Beijing Institute of Big Data Research China School of Mathematical Sciences Peking University China
New estimates for the population risk are established for two-layer neural networks. These estimates are nearly optimal in the sense that the error rates scale in the same way as the Monte Carlo error rates. They are ... 详细信息
来源: 评论
The Athena++ Adaptive Mesh Refinement Framework: Design and Magnetohydrodynamic Solvers
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Astrophysical Journal, Supplement Series 2020年 第1期249卷
作者: Stone, James M. Tomida, Kengo White, Christopher J. Felker, Kyle G. Department of Astrophysical Sciences Princeton University Princeton 08544 NJ United States Program in Applied and Computational Mathematics Princeton University Princeton 08544 NJ United States Department of Earth and Space Science Osaka University Toyonaka Osaka 560-0043 Japan Kavli Institute for Theoretical Physics University of California Santa Barbara Santa Barbara 93107 CA United States School of Natural Sciences Institute for Advanced Study Princeton 08544 NJ United States Astronomical Institute Tohoku University Sendai Miyagi 980-8578 Japan Argonne National Laboratory Lemont 60439 IL United States
The design and implementation of a new framework for adaptive mesh refinement calculations are described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design ... 详细信息
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Regularized matrix data clustering and its application to image analysis
arXiv
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arXiv 2018年
作者: Gao, Xu Shen, Weining Ombao, Hernando Department of Statistics University of California IrvineCA United States Program on Applied Mathematics & Computational Science King Abdullah University of Science and Technology Saudi Arabia
In this paper, we propose a regularized mixture probabilistic model to cluster matrix data and apply it to brain signals. The approach is able to capture the sparsity (low rank, small/zero values) of the original sign... 详细信息
来源: 评论
Solving many-electron Schrödinger equation using deep neural networks
arXiv
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arXiv 2018年
作者: Han, Jiequn Zhang, Linfeng Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Mathematics Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research Beijing100871 China
We introduce a new family of trial wave-functions based on deep neural networks to solve the many-electron Schrödinger equation. The Pauli exclusion principle is dealt with explicitly to ensure that the trial wav... 详细信息
来源: 评论
Recovering Signals from their FROG Trace
Recovering Signals from their FROG Trace
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IEEE International Conference on Acoustics, Speech and Signal Processing
作者: Tamir Bendory Dan Edidin Yonina C. Eldar The Program in Applied and Computational Mathematics Princeton University Princeton NJ USA Department of Mathematics University of Missouri Columbia Missouri USA The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion - Israel Institute of Technology Haifa Israel
The problem of recovering a signal from its power spectrum is called phase retrieval. This problem appears in a variety of scientific applications, such as ultra-short laser pulse characterization and diffraction imag... 详细信息
来源: 评论