Unlocking crowding by ensemble statistics

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This paper introduces a new method for solving the distributed AC power flow (PF) problem by further exploiting the problem formulation. We propose a new variant of the ALADIN algorithm devised specifically for this type of problem. This new variant is cha ...

The performance of SwissSPAD2 (SS2), a large scale, widefield time-gated CMOS SPAD imager developed for fluorescence lifetime imaging, has recently been described in the context of visible range and fluorescence lifetime imaging microscopy (FLIM) of dyes w ...

A central paradigm of self-assembly is to create ordered structures starting from molecular monomers that spontaneously recognize and interact with each other via noncovalent interactions. In recent years, great efforts have been directed toward perfecting ...

A key attribute of persistent or recurring bacterial infections is the ability of the pathogen to evade the host's immune response. Many Enterobacteriaceae express type 1 pili, a pre-adapted virulence trait, to invade host epithelial cells and establish pe ...

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a ...

Nanoparticles (NPs) have wide applications in physical and chemical processes, and their individual properties (e.g., shape, size, and composition) and ensemble properties (e.g., distribution and homogeneity) can significantly affect the performance. Howev ...

We discuss grand canonical simulations based on density-functional theory to study the thermodynamic properties of electrochemical interfaces of metallic electrodes in aqueous environments. Water is represented using implicit solvation, here via the self-c ...

Osteoarthritis (OA) is the most common age-related joint disorder with no effective therapy. According to the World Health Organization, OA affects over 500 million people and is characterized by degradation of cartilage and other joint tissues, severe pai ...

Purpose: In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T-2 relaxation is a powerful and widely appl ...

Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explici ...

Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acqu ...

Single-cell isolation is a truly transformative tool for the understanding of biological systems. It allows single-cell molecular analyses and considers the heterogeneity of cell populations, which is of particular relevance for the diagnosis and treatment ...

In this paper we propose a new, purely algebraic, Petrov-Galerkin reduced basis (RB) method to solve the parametrized Stokes equations, where parameters serve to identify the (variable) domain geometry. Our method is obtained as an algebraic least squares ...

We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space. We prove convergence results with respect to variants of n ...

We study the reactivity and the energy level associated with the reduction of the H2O+ radical cation in liquid water by combining ab initio molecular dynamics simulations at the hybrid functional level, a grand-canonical formulation of solutes in aqueous ...

In this paper, we study regression problems over a separable Hilbert space with the square loss, covering non-parametric regression over a reproducing kernel Hilbert space. We investigate a class of spectral/regularized algorithms, including ridge regressi ...

In this article, we address the numerical solution of the Dirichlet problem for the three-dimensional elliptic Monge-Ampere equation using a least-squares/relaxation approach. The relaxation algorithm allows the decoupling of the differential operators fro ...

In crowding, perception of a target deteriorates in the presence of nearby flankers. Surprisingly, perception can be rescued from crowding if additional flankers are added (uncrowding). Uncrowding is a major challenge for all classic models of crowding and ...

At initialization, artificial neural networks (ANNs) are equivalent to Gaussian processes in the infinite-width limit [12, 9], thus connecting them to kernel methods. We prove that the evolution of an ANN during training can also be described by a kernel: ...

Causal interactions between specific psychiatric symptoms could contribute to the heterogenous clinical trajectories observed in early psychopathology. Current diagnostic approaches merge clinical manifestations that co-occur across subjects and could sign ...

Unlocking crowding by ensemble statistics

Chattez avec Graph Search

Rapid Scalable Distributed Power Flow with Open-Source Implementation

NIR Fluorescence lifetime macroscopic imaging with a time-gated SPAD camera

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

High-Throughput Sizing, Counting, and Elemental Analysis of Anisotropic Multimetallic Nanoparticles with Single-Particle Inductively Coupled Plasma Mass Spectrometry

Grand canonical simulations of electrochemical interfaces in implicit solvation models

Urolithin A improves mitochondrial health, reduces cartilage degeneration, and alleviates pain in osteoarthritis

A new analysis approach for T-2 relaxometry myelin water quantification: Orthogonal Matching Pursuit

i-PI 2.0: A universal force engine for advanced molecular simulations

Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions

Traceable impedance-based single-cell pipetting, from a research set-up to a robust and fast automated robot: DispenCell-S1

An algebraic least squares reduced basis method for the solution of nonaffinely parametrized Stokes equations

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Reactivity and energy level of a localized hole in liquid water

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

A Least-Squares/Relaxation Method for the Numerical Solution of the Three-Dimensional Elliptic Monge-Ampere Equation

Dissecting (un)crowding

Neural Tanget Kernel: Convergence and Generalization in Neural Networks

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing