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Sub-resolution maximum-likelihood based localization of fluorescent nanoparticles in three dimensions

Publications associées (30)

Microscopic Digital Image Correlation Analysis of Strain Distributions in Stainless Steel 316L Induced by Multiaxial Cyclic Loading

Fatigue damage in materials results in localized strain at the microstructural level. In many engineering components of the cooling circuits of nuclear power plants, where austenitic steels are used, the material experiences multiaxial cyclic loading, eith ...

EPFL2023

Stable parameterization of continuous and piecewise-linear functions

Michaël Unser, Joaquim Gonçalves Garcia Barreto Campos, Alexis Marie Frederic Goujon

Rectified-linear-unit (ReLU) neural networks, which play a prominent role in deep learning, generate continuous and piecewise-linear (CPWL) functions. While they provide a powerful parametric representation, the mapping between the parameter and function s ...

2023

An equilibrated flux a posteriori error estimator for defeaturing problems

Ondine Gabrielle Chanon, Annalisa Buffa, Rafael Vazquez Hernandez, Denise Grappein

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

2023

Quantum engineering and detection of advanced radiation beams

Veronica Leccese

Controlling and shaping radiation beams is fundamental for a better understanding of radiation-matter interaction and advancing experimental techniques for material characterization at high spatial resolution. In particular, the current trend in the miniat ...

EPFL2023

Debates on the dorsomedial prefrontal/dorsal anterior cingulate cortex: insights for future research

Nicolas Clairis

The dorsomedial prefrontal cortex/dorsal anterior cingulate cortex (dmPFC/dACC) is a brain area subject to many theories and debates over its function(s). Even its precise anatomical borders are subject to much controversy. In the past decades, the dmPFC/d ...

Oxford Univ Press2023

PROBING INTRACELLULAR ELASTICITY WITH MINIMAL-HESSIAN REGISTRATION

Michaël Unser

We propose an image-based elastography method to measure the heterogeneous stiffness inside a cell and its nucleus. It uses a widely accessible setup consisting of plate compression imaged with fluorescence microscopy. Our framework recovers a spatial map ...

IEEE2023

Microfluidic devices for automated analysis of ingested bacteria in the Caenorhabditis elegans intestine

Farzad Rezaeianaran

In this thesis, we explored on-chip high-resolution imaging of the fate of intestinal bacteria and bacterial products in Caenorhabditis elegans (C. elegans). In the first part, we carried out high-resolution z-stack fluorescent imaging of Red Fluorescent P ...

EPFL2023

High-resolution imaging and analysis of the intestinal bacterial load of Caenorhabditis elegans during early adulthood

Martinus Gijs, Farzad Rezaeianaran

We study the presence within the worm Caenorhabditis elegans (C. elegans) of a fluorescent strain of the worm's bacterial food (Escherichia coli (E. coli) OP50) during early adulthood. Use of a microfluidic chip based on a thin glass coverslip substrate al ...

ROYAL SOC CHEMISTRY2023

Cascaded all-optical quantization employing step-size MMI and shape-optimized power splitter

Xiaowei Zhang, Ye Tian, Jian Wu, Jijun He

As a key unit of future high-throughput communications, optical analog to digital converter (OADC) with all-optical quantizer element that simultaneously possesses high resolution, large bandwidth and compact size is highly promising. A pending issue of co ...

ELSEVIER SCI LTD2023

On double-descent in uncertainty quantification in overparametrized models

Florent Gérard Krzakala, Lenka Zdeborová, Bruno Loureiro, Lucas Andry Clarte, Bruno Loureiro

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

PMLR Proceedings of Machine Learning Research2023