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A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm. A dual mathematical interpretation of the…

Computer Vision and Pattern Recognition · Computer Science 2010-06-16 Guoshen Yu , Guillermo Sapiro , Stéphane Mallat

Compressive sensing (CS) exploits sparsity to recover sparse or compressible signals from dimensionality reducing, non-adaptive sensing mechanisms. Sparsity is also used to enhance interpretability in machine learning and statistics…

Information Theory · Computer Science 2015-07-21 Anastasios Kyrillidis , Luca Baldassarre , Marwa El-Halabi , Quoc Tran-Dinh , Volkan Cevher

The problem of imaging extended targets (sources or scatterers) is formulated in the framework of compressed sensing with emphasis on subwavelength resolution. The proposed formulation of the problems of inverse source/scattering is…

Optics · Physics 2009-09-15 Albert C. Fannjiang

High-throughput computational materials design promises to greatly accelerate the process of discovering new materials and compounds, and of optimizing their properties. The large databases of structures and properties that result from…

Chemical Physics · Physics 2016-11-22 Sandip De , Felix Musil , Teresa Ingram , Carsten Baldauf , Michele Ceriotti

Stress transmission in planar open-cell cellular solids is analysed using a recent theory developed for marginally rigid granular assemblies. This is made possible by constructing a one-to-one mapping between the two systems. General…

Materials Science · Physics 2009-11-07 Raphael Blumenfeld

The paper is devoted to the problem of resonances in one-dimensional disordered systems. Some of the previous results are reviewed and a number of new ones is presented. These results pertain to different models (continuous as well as…

Disordered Systems and Neural Networks · Physics 2015-06-04 Evgeni Gurevich , Boris Shapiro

Multi-phase materials, such as composite materials, exhibit multiple competing failure mechanisms during the growth of a macroscopic defect. For the simulation of the overall fracture process in such materials, we develop a two-phase spring…

Statistical Mechanics · Physics 2020-12-15 Rajat Pratap Singh Parihar , Dhiwakar V. Mani , Anuradha Banerjee , R. Rajesh

Intrinsically disordered proteins and regions are increasingly appreciated for their abundance in the proteome and the many functional roles they play in the cell. In this short review, we describe a variety of approaches used to obtain…

Biological Physics · Physics 2024-12-31 Zi Hao Liu , Maria Tsanai , Oufan Zhang , Teresa Head-Gordon , Julie Forman-Kay

Polaron defects are ubiquitous in materials and play an important role in many processes involving carrier mobility, charge transfer and surface reactivity. Determining the spatial distribution of small polarons is essential to understand…

The availability of big data in materials science offers new routes for analyzing materials properties and functions and achieving scientific understanding. Finding structure in these data that is not directly visible by standard tools and…

We study the propagation of waves in a set of absorbing subwavelength scatterers positioned on a stealth hyperuniform point pattern. We show that spatial correlations in the disorder substantially enhance absorption compared to a fully…

Optics · Physics 2019-03-27 Florian Bigourdan , Romain Pierrat , Rémi Carminati

Bin Packing with Minimum Color Fragmentation (BPMCF) is an extension of the Bin Packing Problem in which each item has a size and a color and the goal is to minimize the sum of the number of bins containing items of each color. In this…

Data Structures and Algorithms · Computer Science 2018-12-04 David Bergman , Carlos Cardonha , Saharnaz Mehrani

The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length and time scales. Many such materials feature inhomogeneous electronic properties with intricate…

Strongly Correlated Electrons · Physics 2023-05-12 S. Basak , M. Alzate Banguero , L. Burzawa , F. Simmons , P. Salev , L. Aigouy , M. M. Qazilbash , I. K. Schuller , D. N. Basov , A. Zimmers , E. W. Carlson

We study statistics of resonances in a one-dimensional disordered chain coupled to an outer world simulated by a perfect lead. We consider a limiting case for weak disorder and derive some results which are new in these studies. The main…

Disordered Systems and Neural Networks · Physics 2012-05-25 Vinayak

We introduce a perturbation expansion for athermal systems that allows an exact determination of displacement fields away from the crystalline state as a response to disorder. We show that the displacement fields in energy minimized…

Soft Condensed Matter · Physics 2021-09-29 Pappu Acharya , Debankur Das , Kabir Ramola

This paper proposes a simple method to distill and detect backdoor patterns within an image: \emph{Cognitive Distillation} (CD). The idea is to extract the "minimal essence" from an input image responsible for the model's prediction. CD…

Machine Learning · Computer Science 2023-09-14 Hanxun Huang , Xingjun Ma , Sarah Erfani , James Bailey

Predicting the densest random disc packing fraction is an unsolved paradigm problem relevant to a number of disciplines and technologies. One difficulty is that it is ill-defined without setting a criterion for the disorder. Another is that…

Statistical Mechanics · Physics 2021-09-15 Raphael Blumenfeld

It has recently been shown that interference effects in disordered systems give rise to two non-trivial structures: the coherent backscattering (CBS) peak, a well-known signature of interference effects in the presence of disorder, and the…

Disordered Systems and Neural Networks · Physics 2021-08-18 Maxime Martinez , Gabriel Lemarié , Bertrand Georgeot , Christian Miniatura , Olivier Giraud

Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent…

Machine Learning · Computer Science 2018-10-16 Aysen Degerli , Sinem Aslan , Mehmet Yamac , Bulent Sankur , Moncef Gabbouj

Among the remarkable scattering properties of correlated disordered materials, the origin of pseudo-gaps and the formation of localized states are some of the most puzzling features. Fundamental differences between scalar and vector waves…

Disordered Systems and Neural Networks · Physics 2021-10-26 R. Monsarrat , R. Pierrat , A. Tourin , A. Goetschy