The importance of priors for l2 regularization and total variation methods in quantitative susceptibility mapping

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The minimization of a data-fidelity term and an additive regularization functional gives rise to a powerful framework for supervised learning. In this paper, we present a unifying regularization functional that depends on an operator L\documentclass[12pt]{ ...

In this paper, we investigate the impact of stochasticity and large stepsizes on the implicit regularisation of gradient descent (GD) and stochastic gradient descent (SGD) over diagonal linear networks. We prove the convergence of GD and SGD with macroscop ...

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

A Phase-contrast imaging (PCI) diagnostic provides measurements of line-integrated electron density fluctuations. Localisation along the laser beam path can be achieved with a spatial filter that selects the wave-vector directions of the fluctuations contr ...

A search for the rare eta -> mu(+)mu(-)mu(+)mu(-) double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integra ...

Context. The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (F ...

The brain is an ultra-soft viscoelastic matrix. Sub-kPa hydrogels match the brain's mechanical properties but are challenging to manipulate in an implantable format. We propose a simple fabrication and processing sequence, consisting of de-hydration, patte ...

In current nanopore-based label-free single-molecule sensing technologies, stochastic processes influence the selection of translocating molecule, translocation rate and translocation velocity. As a result, single-molecule translocations are challenging to ...

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

Modern programs are monolithic, combining code of varied provenance without isolation, all the while running on network-connected devices. A vulnerability in any component may compromise code and data of all other components. Compartmentalization separates ...

Several conductor designs featuring High Temperature Superconducting (HTS) stacked tapes for fusion coils are being proposed. These conductors are planned to operate in time-varying magnetic field and current; thus, the estimation of AC losses is fundament ...

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Very preterm birth (VPT;

The importance of priors for l2 regularization and total variation methods in quantitative susceptibility mapping

Chattez avec Graph Search

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

(S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability

Transfer learning application of self-supervised learning in ARPES

A synthetic phase-contrast imaging diagnostic with spatial filtering for gyrokinetic simulations

Observation of the Rare Decay of the η Meson to Four Muons

Gaia Focused Product Release: Radial velocity time series of long-period variables

Revealing the complexity of ultra-soft hydrogel re-swelling inside the brain

Spatially multiplexed single-molecule translocations through a nanopore at controlled speeds

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

SecureCells: A Secure Compartmentalized Architecture

Impact of Hysteresis Losses in Hybrid (HTS-LTS) Coils for Fusion Applications

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Cortical alterations after very preterm birth and the association with socio-emotional abilities from childhood to early adolescence