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A Functional Perspective on Information Measures

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Random matrix methods for high-dimensional machine learning models

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Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

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RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

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Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

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A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

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This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

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Mott physics in the multiflavored age

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The multiflavor Mott insulators, whose local Hilbert space consists of multiple degrees of freedom, occur widely in both quantum materials and ultracold atom systems. This Comment recommends the review article by Chen and Wu that is, to the author's knowle ...

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Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

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Upcoming wide-field surveys will discover thousands of new strongly lensed quasars which will be monitored with unprecedented cadence by the Legacy Survey of Space and Time (LSST). Many of these quasars will undergo caustic-crossing events over the 10-yr L ...

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Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

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