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Related publications (31)

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Euclid preparation XXI. Intermediate-redshift contaminants in the search for z > 6 galaxies within the Euclid Deep Survey

Yi Wang, Maurizio Martinelli, Frédéric Courbin, Georges Meylan, Hakim Atek, Gianluca Castignani, Austin Chandler Peel

Context. The Euclid mission is expected to discover thousands of z > 6 galaxies in three deep fields, which together will cover a similar to 50 deg(2) area. However, the limited number of Euclid bands (four) and the low availability of ancillary data could ...

EDP SCIENCES S A2022

Stabilized isogeometric discretizations on trimmed and union geometries, and weak imposition of the boundary conditions for the Darcy flow

Riccardo Puppi

Modern manufacturing engineering is based on a ``design-through-analysis'' workflow. According to this paradigm, a prototype is first designed with Computer-aided-design (CAD) software and then finalized by simulating its physical behavior, which usually i ...

EPFL2022

Finding symmetry breaking order parameters with Euclidean neural networks

Mario Geiger

Curie's principle states that "when effects show certain asymmetry, this asymmetry must be found in the causes that gave rise to them." We demonstrate that symmetry equivariant neural networks uphold Curie's principle and can be used to articulate many sym ...

AMER PHYSICAL SOC2021

Switchover phenomenon induced by epidemic seeding on geometric networks

Gergely Odor

It is a fundamental question in disease modeling how the initial seeding of an epidemic, spreading over a network, determines its final outcome. One important goal has been to find the seed configuration, which infects the most individuals. Although the id ...

2021

Resources for the article "Investigating the role of educational robotics in formal mathematics education"

Barbara Bruno, Laila Abdelsalam El-Hamamsy, Jérôme Guillaume Brender

This repository contains the material required to reproduce the study looking to investigate the role of educational robotics in formal mathematics education for 15 year old students in the French speaking region of Switzerland. This includes : Pedagogical ...

2021

Local invertibility and sensitivity of atomic structure-feature mappings

Michele Ceriotti, Sergey Pozdnyakov

Background: The increasingly common applications of machine-learning schemes to atomic-scale simulations have triggered efforts to better understand the mathematical properties of the mapping between the Cartesian coordinates of the atoms and the variety o ...

2021

Mathematical and numerical models for the cardiac electromechanical function

Alfio Quarteroni, Francesco Regazzoni

This paper deals with the mathematical model that describes the function of the human heart. More specifically, it addresses the equations that express the electromechanical process, that is the mechanical deformation (contraction and relaxation) of the he ...

EUROPEAN MATHEMATICAL SOC-EMS2021

A method for faster application of process integration techniques in retrofit situations

Tuong-Van Nguyen

Numerous process integration techniques were proved to be highly effective for identifying and estimating potential energy savings in the industry. However, they require high time and effort to collect and analyse process data. As a result, they do not con ...

ELSEVIER SCI LTD2021

Adaptive Laser Welding Control: A Reinforcement Learning Approach

Giulio Masinelli, Silvio Zanoli

Despite extensive research efforts in the field of laser welding, the imperfect repeatability of the weld quality still represents an open topic. Indeed, the inherent complexity of the underlying physical phenomena prevents the implementation of an effecti ...

2020

Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

Matthew Josef Parkan

The thesis presented hereby proposes as a general objective the estimation of forest inventory parameters (e.g. trunk location, height, basal area, crown area, species, etc..) from the combination of Airborne Laser Scanning (ALS) and Hyperspectal Imaging ( ...

EPFL2019

Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity

Anne-Clémence Corminboeuf, Alberto Fabrizio, Andrea Grisafi, Ksenia Briling

Machine-learning in quantum chemistry is currently booming, with reported applications spanning all molecular properties from simple atomization energies to complex mathematical objects such as the many-body wavefunction. Due to its central role in density ...

2020