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The jamming transition of particles with finite-range interactions is characterized by a variety of critical phenomena, including power law distributions of marginal contacts. We numerically study a recently proposed simple model of…

Statistical Mechanics · Physics 2016-01-20 Yoav Kallus

We experimentally study the jamming of quasi-two-dimensional emulsions. Our experiments consist of oil-in-water emulsion droplets confined between two parallel plates. From the droplet outlines, we can determine the forces between every…

Soft Condensed Matter · Physics 2013-02-28 Kenneth W. Desmond , Pearl J. Young , Dandan Chen , Eric R. Weeks

By building upon the recent theory that established the connection between implicit generative modeling (IGM) and optimal transport, in this study, we propose a novel parameter-free algorithm for learning the underlying distributions of…

Machine Learning · Statistics 2019-06-12 Antoine Liutkus , Umut Şimşekli , Szymon Majewski , Alain Durmus , Fabian-Robert Stöter

We consider linear regression in the high-dimensional regime where the number of observations $n$ is smaller than the number of parameters $p$. A very successful approach in this setting uses $\ell_1$-penalized least squares (a.k.a. the…

Methodology · Statistics 2014-02-05 Adel Javanmard , Andrea Montanari

We develop a scaling theory of the unjamming transition of soft frictionless disks in two dimensions by defining local areas, which can be uniquely assigned to each contact. These serve to define local order parameters, whose distribution…

Disordered Systems and Neural Networks · Physics 2017-03-29 Kabir Ramola , Bulbul Chakraborty

Using Bayesian experimental design techniques, we have shown that for a single two-level quantum mechanical system under strong (projective) measurement, the dynamical parameters of a model Hamiltonian can be estimated with exponentially…

Quantum Physics · Physics 2012-06-05 Christopher Ferrie , Christopher E. Granade , D. G. Cory

Inverse design refers to the problem of optimizing the input of an objective function in order to enact a target outcome. For many real-world engineering problems, the objective function takes the form of a simulator that predicts how the…

Le Cam's method (or the two-point method) is a commonly used tool for obtaining statistical lower bound and especially popular for functional estimation problems. This work aims to explain and give conditions for the tightness of Le Cam's…

Statistics Theory · Mathematics 2021-01-05 Yury Polyanskiy , Yihong Wu

Soft, disordered, micro-structured materials are ubiquitous in nature and industry, and are different from ordinary fluids or solids, with unusual, interesting static and flow properties. The transition from fluid to solid -at the so-called…

Soft Condensed Matter · Physics 2016-07-12 Nishant Kumar , Stefan Luding

Jump Markov linear systems (JMLS) are a useful class which can be used to model processes which exhibit random changes in behavior during operation. This paper presents a numerically stable method for learning the parameters of jump Markov…

Applications · Statistics 2020-04-21 Mark P. Balenzuela , Adrian G. Wills , Christopher Renton , Brett Ninness

Estimation frameworks for statistical inference are preferred to hypothesis testing when quantifying uncertainty and precise estimation are more valuable than binary decisions about statistical significance. Study design for…

Methodology · Statistics 2025-10-29 Luke Hagar , Nathaniel T. Stevens

Optimum designs for parameter estimation in generalized regression models are standardly based on the Fisher information matrix (cf. Atkinson et al (2014) for a recent exposition). The corresponding optimality criteria are related to the…

Statistics Theory · Mathematics 2015-07-28 Katarína Burclová , Andrej Pázman

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

Parameter estimation is one of the most important tasks in statistics, and is key to helping people understand the distribution behind a sample of observations. Traditionally parameter estimation is done either by closed-form solutions…

Machine Learning · Computer Science 2024-03-04 Xiaoxin Yin , David S. Yin

Many networking applications require timely access to recent network measurements, which can be captured using a sliding window model. Maintaining such measurements is a challenging task due to the fast line speed and scarcity of fast…

Data Structures and Algorithms · Computer Science 2018-04-25 Ran Ben Basat , Gil Einziger , Roy Friedman

The optimal selection of experimental conditions is essential to maximizing the value of data for inference and prediction, particularly in situations where experiments are time-consuming and expensive to conduct. We propose a general…

Machine Learning · Statistics 2012-12-04 Xun Huan , Youssef M. Marzouk

This work deals with an inverse two-dimensional nonlinear heat conduction problem to determine the top and lateral surface transfer coefficients. For this, the \textsc{B}ayesian framework with the \textsc{M}arkov Chain \textsc{M}onte…

Computational Engineering, Finance, and Science · Computer Science 2022-06-20 Julien Berger , Clemence Legros

Ensuring a smooth rate of efflux of particles from an outlet without unpredictable clogging events is crucial in processing powders and grains. We show by experiments and simulations that an obstacle placed near the outlet can greatly…

Soft Condensed Matter · Physics 2024-11-19 Abhijit Sinha , Jackson Diodati , Narayanan Menon , Shubha Tewari , Shankar Ghosh

Motivated by the need to localise faults along electrical power lines, this paper adopts a frequency-domain approach to parameter estimation for an infinite-dimensional linear dynamical system with one spatial variable. Since the time of…

Systems and Control · Electrical Eng. & Systems 2023-10-23 Daniel Selvaratnam , Amritam Das , Henrik Sandberg

A novel probabilistic approach for the design of mechanical structures with friction interfaces is proposed. The objective function is defined as the probability that a specified performance measure of the forced vibration response is…

Computational Engineering, Finance, and Science · Computer Science 2021-01-01 Malte Krack , Sebastian Tatzko , Lars Panning-von Scheidt , Jörg Wallaschek
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