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检索条件"机构=Department of Geosciences and Program in Applied and Computational Mathematics"
859 条 记 录,以下是371-380 订阅
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NOMAD: Nonlinear Manifold Decoders for Operator Learning
arXiv
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arXiv 2022年
作者: Seidman, Jacob H. Kissas, Georgios Perdikaris, Paris Pappas, George J. Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania United States Department of Electrical and Systems Engineering University of Pennsylvania United States
Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By di... 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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Multireference alignment is easier with an aperiodic translation distribution
arXiv
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arXiv 2017年
作者: Abbe, Emmanuel Bendory, Tamir Leeb, William Pereira, João M. Sharon, Nir 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
In the multireference alignment model, a signal is observed by the action of a random circular translation and the addition of Gaussian noise. The goal is to recover the signal's orbit by accessing multiple indepe... 详细信息
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First-principles characterization of Ni diffusion kinetics in β-NiAl
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Physical Review B 2008年 第18期78卷 184105-184105页
作者: Kristen A. Marino Emily A. Carter Department of Chemical Engineering Princeton University Princeton New Jersey 08544-5263 USA Department of Mechanical and Aerospace Engineering and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544-5263 USA
First-principles density functional theory calculations are performed to examine five postulated diffusion mechanisms for Ni in NiAl: next-nearest-neighbor (NNN) jumps, the triple defect mechanism, and three variants ...
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Comment on “Jamming at zero temperature and zero applied stress: The epitome of disorder”
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Physical Review E 2004年 第4期70卷 043301-043301页
作者: Aleksandar Donev Salvatore Torquato Frank H. Stillinger Robert Connelly Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA Materials Institute Princeton University Princeton New Jersey 08544 USA Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Mathematics Cornell University Ithaca New York 14853 USA
O’Hern, Silbert, Liu, and Nagel [Phys. Rev. E. 68, 011306 (2003)] claim that a special point J of a “jamming phase diagram” (in density, temperature, stress space) is related to random close packing of hard spheres... 详细信息
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Ab Initio Generalized Langevin Equation
arXiv
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arXiv 2022年
作者: Xie, Pinchen Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry Department of Physics Program in Applied and Computational Mathematics Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States AI for Science Institute Beijing China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing China
We introduce a machine learning-based approach called ab initio generalized Langevin equation (AIGLE) to model the dynamics of slow collective variables in materials and molecules. In this scheme, the parameters are l... 详细信息
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DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
arXiv
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arXiv 2017年
作者: Wang, Han Zhang, Linfeng Han, Jiequn Weinan, E. Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China CAEP Software Center for High Performance Numerical Simulation Huayuan Road 6 Beijing100088 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Center for Data Science Beijing International Center for Mathematical Research Peking University Beijing Institute of Big Data Research Beijing100871 China
Recent developments in many-body potential energy representation via deep learning have brought new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Here we describe DeePMD-kit, a p... 详细信息
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Benchmark problems for phase retrieval
arXiv
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arXiv 2017年
作者: Elser, Veit Lan, Ti-Yen Bendory, Tamir Department of Physics Cornell University IthacaNY14853-2501 United States Program in Applied and Computational Mathematics Princeton University Princeton08544-1000 United States
In recent years, the mathematical and algorithmic aspects of the phase retrieval problem have received considerable attention. Many papers in this area mention crystallography as a principal application. In crystallog... 详细信息
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Bayesian Spectral Graph Denoising with Smoothness Prior
Bayesian Spectral Graph Denoising with Smoothness Prior
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Annual Conference on Information Sciences and Systems (CISS)
作者: Sam Leone Xingzhi Sun Michael Perlmutter Smita Krishnaswamy Program for Applied Mathematics Yale University Department of Computer Science Yale University Department of Mathematics Boise State University Department of Genetics Yale School of Medicine Wu Tsai Institute Yale University FAIR Meta AI Computational Biology and Bioinformatics Program Yale University
Here we consider the problem of denoising features associated to complex data, modeled as signals on a graph, via a smoothness prior. This is motivated in part by settings such as single-cell RNA where the data is ver...
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A fourth-order accurate finite volume method for ideal mhd via upwind constrained transport
arXiv
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arXiv 2017年
作者: Felker, Kyle Gerard Stone, James Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States
We present a fourth-order accurate finite volume method for the solution of ideal magnetohydrodynamics (MHD). The numerical method combines high-order quadrature rules in the solution of semi-discrete formulations of ... 详细信息
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