VIVALDI: steel billet tracking with advanced computer vision

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ShapeNet: Shape constraint for galaxy image deconvolution

Utsav Akhaury

Deep learning (DL) has shown remarkable results in solving inverse problems in various domains. In particular, the Tikhonet approach is very powerful in deconvolving optical astronomical images. However, this approach only uses the l(2) loss, which does no ...

2022

what If...? Pandemic Policy-decision-support to Guide a Cost-benefit-optimised, Country- Specific Response

Francesco Posa, Lucas Christophe Massemin, Giorgio Mannarini, Martin Jaggi, Mary-Anne Hartley, Tatjana Chavdarova, Prakhar Gupta, Thierry Bossy

Background After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiol ...

PUBLIC LIBRARY SCIENCE2022

Thermodynamics and dielectric response of BaTiO3 by data-driven modeling

Nicola Marzari, Michele Ceriotti, Giovanni Pizzi, Michele Kotiuga, Max David Veit, Lorenzo Gigli

Modeling ferroelectric materials from first principles is one of the successes of density-functional theory and the driver of much development effort, requiring an accurate description of the electronic processes and the thermodynamic equilibrium that driv ...

NATURE PORTFOLIO2022

The Microstructural Features of the Diffusion-Simulated Connectivity (DiSCo) Dataset

Jean-Philippe Thiran, Gabriel Girard, Marco Pizzolato, Jonathan Rafael Patino Lopez

We present a detailed description of the structural characteristics of the MICCAI 2021 Diffusion Simulated Connectivity (DiSCo) Challenge synthetic dataset. The DiSCo dataset are one of a kind numerical phantoms for the simulation of the diffusion-weighted ...

SPRINGER INTERNATIONAL PUBLISHING AG2021

Impact of Data Processing on Fairness in Supervised Learning

Negar Kiyavash

We study the impact of pre and postprocessing for reducing discrimination in data-driven decision makers. We first analyze the fundamental trade-off between fairness and accuracy in a preprocessing approach, and propose a design for a preprocessing module ...

IEEE2021

Bayesian probabilistic assignment of chemical shifts in organic solids

David Lyndon Emsley, Michele Ceriotti, Manuel Cordova, Bruno Simões de Almeida, Martins Balodis

A prerequisite for NMR studies of organic materials is assigning each experimental chemical shift to a set of geometrically equivalent nuclei. Obtaining the assignment experimentally can be challenging and typically requires time-consuming multidimensional ...

2021

Convergence without Convexity: Sampling, Optimization, and Games

Ya-Ping Hsieh

Many important problems in contemporary machine learning involve solving highly non- convex problems in sampling, optimization, or games. The absence of convexity poses significant challenges to convergence analysis of most training algorithms, and in some ...

EPFL2020

Occupancy detection and tracking in buildings using floor-vibration signals

Slah Drira

In sensed buildings, information related to occupant movement helps optimize important functionalities such as security enhancement, energy management, and caregiving. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. The ...

EPFL2020

Accurate molecular polarizabilities with coupled cluster theory and machine learning

Michele Ceriotti, David Mark Wilkins, Andrea Grisafi

The molecular dipole polarizability describes the tendency of a molecule to change its dipole moment in response to an applied electric field. This quantity governs key intra- and intermolecular interactions, such as induction and dispersion; plays a vital ...

2019