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We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as the original observation, up to a (known) scaling of a…

Methodology · Statistics 2023-11-22 Anna Neufeld , Ameer Dharamshi , Lucy L. Gao , Daniela Witten

When computing quantum-mechanical observables, the ``curse of dimensionality'' limits the naive approach that uses the quantum-mechanical wavefunction. The semiclassical Herman--Kluk propagator mitigates this curse by employing a grid-free…

Numerical Analysis · Mathematics 2024-08-02 Fabian Kröninger , Caroline Lasser , Jiri J. L. Vanicek

Learning-based synthetic multi-contrast MRI commonly involves deep models trained using high-quality images of source and target contrasts, regardless of whether source and target domain samples are paired or unpaired. This results in…

Image and Video Processing · Electrical Eng. & Systems 2021-05-13 Mahmut Yurt , Salman Ul Hassan Dar , Muzaffer Özbey , Berk Tınaz , Kader Karlı Oğuz , Tolga Çukur

Subspace clustering is a useful technique for many computer vision applications in which the intrinsic dimension of high-dimensional data is often smaller than the ambient dimension. Spectral clustering, as one of the main approaches to…

Machine Learning · Computer Science 2018-03-16 Lei Zhou , Xiao Bai , Xianglong Liu , Jun Zhou , Hancock Edwin

Raman spectroscopy and Second Harmonic Generation (SHG) are complementary, non-destructive techniques that provide rich and distinct insights into the structural and electronic properties of materials. Raman spectroscopy offers detailed…

Optics · Physics 2026-04-30 Volodymyr Multian , Luigi Bonacina , Jérémie Teyssier

Recently, multi-instrument music generation has become a hot topic. Different from single-instrument generation, multi-instrument generation needs to consider inter-track harmony besides intra-track coherence. This is usually achieved by…

Sound · Computer Science 2023-05-29 Xipin Wei , Junhui Chen , Zirui Zheng , Li Guo , Lantian Li , Dong Wang

The correlation of odd electrons in graphene turns out to be significant so that the species should be attributed to correlated ones. This finding profoundly influences the computational strategy addressing it to multireference…

Materials Science · Physics 2012-01-27 E. F. Sheka

The linear and nonlinear dynamical susceptibilities of a two level system are calculated as it undergoes a transition to a decoherent state. Analogously to the Glover-Tinkham-Ferrell sum rule of superconductivity, spectral weight in the…

Condensed Matter · Physics 2009-10-31 Gregory Levine

The linear energy dispersion of graphene electrons leads to a strongly nonlinear electromagnetic response of this material. We develop a general quantum theory of the third-order nonlinear local dynamic conductivity of graphene…

Mesoscale and Nanoscale Physics · Physics 2016-02-04 S. A. Mikhailov

Clustering serves as a vital tool for uncovering latent data structures, and achieving both high accuracy and interpretability is essential. To this end, existing methods typically construct binary decision trees by solving mixed-integer…

Machine Learning · Computer Science 2026-02-17 Hayato Suzuki , Shunnosuke Ikeda , Yuichi Takano

High-order harmonic generation (HHG) in aligned linear molecules can offer valuable information about strong-field interactions in lower-lying molecular orbitals, but extracting this information is difficult for three-dimensional molecular…

The object of this work is the numerical investigation of a non-commutative field theory defined via the spectral action principle. The Starting point is a spectral triple (A,H,D) referred to as harmonic. The construction of these data…

Mathematical Physics · Physics 2011-11-15 Bernardino Spisso

We discuss how recently discovered techniques and tools from compressed sensing can be used in tensor decompositions, with a view towards modeling signals from multiple arrays of multiple sensors. We show that with appropriate bounds on a…

Numerical Analysis · Mathematics 2015-05-18 Lek-Heng Lim , Pierre Comon

The complex spectropolarimetric patterns around strong chromospheric lines, the result of subtle spectroscopic and transport mechanisms, are sensitive, sometimes in unexpected ways, to the presence of magnetic fields in the chromosphere,…

Solar and Stellar Astrophysics · Physics 2017-10-12 R. Manso Sainz , T. del Pino Alemán , R. Casini

Kink model is developed to analyze the data where the regression function is twostage linear but intersects at an unknown threshold. In quantile regression with longitudinal data, previous work assumed that the unknown threshold parameters…

Methodology · Statistics 2020-09-07 Chuang Wan

We employ transformation optics to study analytically nonlinear wave mixing from a singular geometry of touching plasmonic wires. We obtain the analytic solution of the near-field and complement it with a solution of the far-field…

Optics · Physics 2021-05-05 Shimon Elkabetz , K. Nireekshan Reddy , Y. Sivan

Extending a result of He to the non-integrable case of K-contact manifolds, it is shown that transverse Hermitian scalar curvature may be interpreted as a moment map for the strict contactomorphism group. As a consequence, we may generalize…

Differential Geometry · Mathematics 2014-10-07 Mehdi Lejmi , Markus Upmeier

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for…

Signal Processing · Electrical Eng. & Systems 2020-12-09 Devis Tuia , Diego Marcos , Gustau Camps-Valls

We calculate the linear and nonlinear optical properties of the Falicov-Kimball model for a mixed-valent system within the self-consistent mean-field approximation. Second-harmonic generation can only occur if the mixed-valent state has a…

Condensed Matter · Physics 2009-10-28 T. Portengen , Th. Ostreich , L. J. Sham

Many nonparametric regressors were recently shown to converge at rates that depend only on the intrinsic dimension of data. These regressors thus escape the curse of dimension when high-dimensional data has low intrinsic dimension (e.g. a…

Machine Learning · Statistics 2011-10-20 Samory Kpotufe