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Bayesian shrinkage methods have generated a lot of recent interest as tools for high-dimensional regression and model selection. These methods naturally facilitate tractable uncertainty quantification and incorporation of prior information.…

Methodology · Statistics 2017-04-21 Bala Rajaratnam , Doug Sparks , Kshitij Khare , Liyuan Zhang

This paper presents a novel method for structural data recognition using a large number of graph models. In general, prevalent methods for structural data recognition have two shortcomings: 1) Only a single model is used to capture…

Machine Learning · Computer Science 2020-04-15 Tomo Miyazaki , Shinichiro Omachi

The roughness properties of two-dimensional fracture surfaces as created by the slow failure of random fuse networks are considered and compared to yield surfaces of perfect plasticity with similar disorder. By studying systems up to a…

Statistical Mechanics · Physics 2009-10-31 E. T. Seppala , V. I. Raisanen , M. J. Alava

Modeling folding surfaces with nonzero thickness is of practical interest for mechanical engineering. There are many existing approaches that account for material thickness in folding applications. We propose a new systematic and broadly…

Computational Geometry · Computer Science 2016-01-22 Jason S. Ku , Erik D. Demaine

Ecology studies biodiversity in its variety and complexity. It describes how species distribute and perform in response to environmental changes. Ecological processes and structures are highly complex and adaptive. In order to quantify…

Populations and Evolution · Quantitative Biology 2013-10-09 Cang Hui

Scattering resonances play a crucial role in understanding wave behavior in various physical systems. While significant progress has been made in analyzing resonances in high-contrast and nonlinear media, a general characterization of…

Optics · Physics 2024-10-29 Taoufik Meklachi

This document gives a historical review of the scaling of particles yields emitted from excited nuclei. The focus will be on what scaling is, what can be learned from scaling, the underlying theory of why one might expect particle yields to…

Nuclear Experiment · Physics 2007-05-23 James B. Elliott , Kyrill A. Bugaev , Luciano G. Moretto , Larry Phair

A constitutive model is presented for brittle granular materials based on a recent reformulation of the breakage mechanics theory. Compared with previous breakage mechanics-based models, the proposed model is improved to capture strain…

Soft Condensed Matter · Physics 2019-02-21 M. B. Cil , R. C. Hurley , L. Graham-Brady

The particle discrete element simulation of the instability and failure process of the granular slope accumulator model when the metal plate continues downward is obtained, and the two-dimensional total velocity vector of soil particle…

Geophysics · Physics 2020-10-02 Shengdong Zhang , Shihui You , Longfei Chen , Xiaofei Liu

In this paper we establish new simple local geometric criteria for discrete entropic curvature introduced in [47] that are powerful enough to capture many geometric properties of complex models arising in mathematical physics. These results…

Probability · Mathematics 2024-07-01 Martin Rapaport , Paul-Marie Samson

We have studied shrinkage crack patterns which form when a thin layer of an alumina/water slurry dries. Both isotropic and directional drying were studied. The dynamics of the pattern formation process and the geometric properties of the…

patt-sol · Physics 2009-10-31 Kelly A. Shorlin , John R. de Bruyn , Malcolm Graham , Stephen W. Morris

Utilizing recently developed abstract notions of sectional curvature, we introduce a method for constructing a curvature-based geometric profile of discrete metric spaces. The curvature concept that we use here captures the metric relations…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Charlotte Beylier , Parvaneh Joharinad , Jürgen Jost , Nahid Torbati

This paper introduces a simple principle for robust high-dimensional statistical inference via an appropriate shrinkage on the data. This widens the scope of high-dimensional techniques, reducing the moment conditions from sub-exponential…

Statistics Theory · Mathematics 2017-05-08 Jianqing Fan , Weichen Wang , Ziwei Zhu

When cracks form in a thin contracting layer, they sequentially break the layer into smaller and smaller pieces. A rectilinear crack pattern encodes information about the order of crack formation, as later cracks tend to intersect with…

Geophysics · Physics 2015-09-25 Lucas Goehring

In high-dimensional data analysis, regularization methods pursuing sparsity and/or low rank have received a lot of attention recently. To provide a proper amount of shrinkage, it is typical to use a grid search and a model comparison…

Methodology · Statistics 2019-01-01 Yiyuan She , Hoang Tran

We study the surface roughness of prototype models displaying self-organized criticality (SOC) and their noncritical variants in one dimension. For SOC systems, we find that two seemingly equivalent definitions of surface roughness yields…

Statistical Mechanics · Physics 2009-11-10 J. G. Oliveira , J. F. F. Mendes , G. Tripathy

Understanding the structure and dynamics of liquids is pivotal for the study of larger spatiotemporal processes, especially in glass-forming materials at low temperatures. Density scaling, observed in many molecular systems through…

Soft Condensed Matter · Physics 2024-10-29 Jaehyeok Jin , David R. Reichman , Jeppe C. Dyre , Ulf R. Pedersen

Impact craters are among the most prominent topographic features on planetary bodies. Crater scaling laws allow us to extract information about the impact histories on the host bodies. The pi-group scaling laws have been constructed based…

Earth and Planetary Astrophysics · Physics 2018-08-15 Kosuke Kurosawa , Satoshi Takada

Reconstructing the missing parts of a curve has been the subject of much computational research, with applications in image inpainting, object synthesis, etc. Different approaches for solving that problem are typically based on processes…

Computer Vision and Pattern Recognition · Computer Science 2018-06-14 Ehud Barnea , Ohad Ben-Shahar

Soft-thresholding is a sparse modeling method that is typically applied to wavelet denoising in statistical signal processing and analysis. It has a single parameter that controls a threshold level on wavelet coefficients and,…

Methodology · Statistics 2016-02-01 Katsuyuki Hagiwara
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