Publications associées à Iterative FBP For Improved Reconstruction Of X-Ray Differential Phase-Contrast Tomograms

CONTROL OF HYPERBOLIC AND PARABOLIC EQUATIONS ON NETWORKS AND SINGULAR LIMITS

vanishing viscosity, networks. This work has received funding from the Alexander von Humboldt-Professorship program, the Transregio 154 Project "Mathematical Modelling, Simulation and Optimization Using the Example of Gas Networks" of the DFG, the grant PI ...

Amer Inst Mathematical Sciences-Aims2024

Towards Trustworthy Deep Learning for Image Reconstruction

Alexis Marie Frederic Goujon

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

EPFL2024

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

3D printed large amplitude torsional microactuators powered by ultrasound

Mehdi Ali Gadiri, Mahmut Selman Sakar, Amit Yedidia Dolev, Junsun Hwang

Here, we introduce a design, fabrication, and control methodology for large amplitude torsional microactuators powered by ultrasound. The microactuators are 3D printed from two polymers with drastically different elastic moduli as a monolithic compliant me ...

2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Exploring Novel Modalities for Optical Diffraction Tomography

Amirhossein Saba Shirvan

In the past decade, optical diffraction tomography has gained a lot of attention for its ability to create label-free three-dimensional (3D) images of the refractive index distribution of biological samples using scattered fields measured through holograph ...

EPFL2023

Deep Learning Meets Sparse Regularization

Rahul Parhi

Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of ...

2023

Maximum likelihood bolometry for ASDEX upgrade experiments

Olivier Claude Martin Février, Riccardo Rossi

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, h ...

Iop Publishing Ltd2023

An optimal preconditioned FFT-accelerated finite element solver for homogenization

Till Junge, Ali Falsafi, Martin Ladecký

We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

ELSEVIER SCIENCE INC2023

Correlating cryo-super resolution radial fluctuations and dual-axis cryo-scanning transmission electron tomography to bridge the light-electron resolution gap

Prabhu Prasad Swain

Visualization of organelles and their interactions with other features in the native cell remains a challenge in modern biology. We have introduced cryo-scanning transmission electron tomography (CSTET), which can ac-cess 3D volumes on the scale of 1 micro ...

Elsevier2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

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

Phase Retrieval: From Computational Imaging to Machine Learning: A tutorial

Michaël Unser, Thanh-An Michel Pham, Jonathan Yuelin Dong

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches involve techniqu ...

2023

Dynamics of CLIMP-63 S-acylation control ER morphology

Kathryn Hess Bellwald, Béatrice Kunz, Graham Knott, Françoise Gisou van der Goot Grunberg, Laurence Gouzi Abrami, Vassily Hatzimanikatis, Patrick Alain Sandoz, Robin Alexander Denhardt-Eriksson, Sylvia Ho, Luciano Andres Abriata, Catherine Maclachlan, Gard Spreemann

A key player in the formation of endoplasmic reticulum sheets is CLIMP-63, but mechanistic details remained elusive. Here authors combined cellular experiments and mathematical modelling to show that S-acylation of CLIMP-63 regulates its function by mediat ...

Nature Portfolio2023

Practical computational imaging by use of spatiotemporal light modulation: from simulations to applications in biological microscopy

François Thierry M Marelli

Optical microscopy is an essential tool for biologists, who are often faced with the need to overcome the spatial and temporal resolution limitations of their devices to capture finer details. As upgrading imaging hardware is expensive, computational metho ...

EPFL2023

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

On the similarity between aortic and carotid pressure diastolic decay: a mathematical modelling study

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas, Sokratis Anagnostopoulos

Aortic diastolic pressure decay (DPD) has been shown to have considerable pathophysiological relevance in the assessment of vascular health, as it is significantly affected by arterial stiffening. Nonetheless, the aortic pressure waveform is rarely availab ...

Nature Portfolio2023

Landscapes of DNA Mechanics and Genomes

Thomas Antonin Zwahlen

The local physical properties - such as shape and flexibility - of the DNA double-helix is today widely believed to be influenced by nucleic acid sequence in a non-trivial way. Furthermore, there is strong evidence that these properties play a role in many ...

EPFL2023

Beyond undulation! Body morphology and sensing components of elongated animals and robots reveal skills to maintain competent locomotion

Laura Isabel Paez Coy

Locomotion is an essential evolutive innovation of living beings that allows them to colonize and dominate the planet. As diverse as animal morphologies are (living) and were (extinct), their locomotion modalities are also diverse. In particular, animal mo ...

EPFL2023

Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: An application to the Italian scenario

Alfio Quarteroni, Nicola Parolini, Luca Dede'

In the context of SARS-CoV-2 pandemic, mathematical modelling has played a funda-mental role for making forecasts, simulating scenarios and evaluating the impact of pre-ventive political, social and pharmaceutical measures. Optimal control theory represent ...

KEAI PUBLISHING LTD2023