Dear all,
We are offering an internship position for 4 to 6 months at the University of Luxembourg, in the Legato team led by Prof. Stéphane P.A. Bordas (FLSW). The subject deals with implementing the IsoGeometric Analysis in the SOFA Framework. Join a dynamic team and an open-source consortium! More details are provided in the attached document.
Legato group
Lorella Viola: The problem with GPT for the Humanities (and for humanity)

Machine Learning Seminar presentation
Topic: The problem with GPT for the Humanities (and for humanity).
Speaker: Lorella Viola, Luxembourg Centre for Contemporary and Digital History (C2DH ), University of Luxembourg
Time: Wednesday, 2022.05.11, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Abstract:
Additional material:
Video recording: https://youtu.be/J1zkS1mKGlE
Mauro Dalle Lucca Tosi: TensAIR: an asynchronous and decentralized framework to distribute artificial neural networks training

Machine Learning Seminar presentation
Topic: TensAIR: an asynchronous and decentralized framework to distribute artificial neural networks training
Speaker: Mauro Dalle Lucca Tosi, Faculty of Science, Technology and Medicine; University of Luxembourg
Time: Wednesday, 2021.09.15, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Abstract:
In the last decades, artificial neural networks (ANNs) have drawn academy and industry attention for their ability to represent and solve complex problems. ANNs use algorithms based on stochastic gradient descent (SGD) to learn data patterns from training examples, which tends to be time-consuming. Researchers are studying how to distribute this computation across multiple GPUs to reduce training time. Modern implementations rely on synchronously scaling up resources or asynchronously scaling them out using a centralized communication network. However, both of these approaches have communication bottlenecks, which may impair their scaling time. In this research, we create TensAIR, a framework that scales out the training of sparse ANNs models in an asynchronously and decentralized manner. Due to the commutative properties of SGD updates, we linearly scaled out the number of gradients computed per second with minimal impairment on the convergence of the models – relative to the models’ sparseness. These results indicate that TensAIR enables the training of sparse neural networks in significantly less time. We conjecture that this article may inspire further studies on the usage of sparse ANNs on time-sensitive scenarios like online machine learning, which until now would not be considered feasible.
Additional material:
GRACM 2021: Fracture across space and time: a journey through multiscale methods, model order reduction and machine learning

Dr. Katerina E. Aifantis: Mechanical Behavior of Cells and Biomaterials 06/30/21 at 11:00 am

Workshop on “Image and Physics” on June 18, 2021, Center of Mathematical Morphology and Center of Materials

We are pleased to announce a workshop centered on “image and physics” on June 18, 2021, organized by the Center of Mathematical Morphology and Center of Materials, devoted to image analysis, deep learning, physics, and material science. The main objective of this event is to promote exchanges in an informal setting between researchers of MINES ParisTech working on image analysis and deep learning, on the one hand, and on physics and material science in general. You are welcome to send your contributions (title, authors, and abstract) to the organizers before June 4th.
We hope to see you in June,
François Willot et Henry Proudhon
18/06/2021 at 9:30.link : https://mines-paristech.zoom.us/j/92437426470?pwd=YWlIblpndkRRTlQyQXpZK1pJaXY4QT09
<https://mines-paristech.zoom.us/j/92437426470?pwd=YWlIblpndkRRTlQyQXpZK1pJaXY4QT09>
(ID de la réunion / Meeting ID : 92437426470 Mot de passe / Password :
280307)
MMLDT-CSET 2021 NSF Fellowship Application and registration

Research Associate (Postdoc) in Reduced Order Modelling for Urban Wind Flow Application

Hichem Omrani: Predicting air pollution using remote sensing and sensors measurement

Machine Learning Seminar presentation
Topic: Predicting air pollution using remote sensing and sensors measurement
Speaker: Hichem Omrani, Luxembourg Institute of Socio-Economic Research (LISER)
Time: Wednesday, 2021.03.31, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Abstract:
Air pollution is a threat to public health, having negative effects on human health and well-being. This research seminar aims to (1) predict air pollution at a fine spatial resolution using the “land use regression” model, (2) assess population exposure to air population in Luxembourg and its surrounding areas, (3) and discuss ongoing work, opportunities and challenges for future research.
Additional material:
Gabriele Pozzetti: An Industry view on ML: CERATIZIT technology landscape and the art of collaborating with an industrial partner.
Machine Learning Seminar presentation
Topic: An Industry view on ML: CERATIZIT technology landscape and the art of collaborating with an industrial partner.
Speaker: Gabriele Pozzetti, Manager \ Artificial Intelligence and Data Science \ CERATIZIT
Time: Wednesday, 2021.03.24, 10:00 CET
How to join: Please contact Jakub Lengiewicz
Abstract:
The difference between theory and practice is that in theory the two will mostly agree, in practice they will not.
CERATIZIT is a global player in high-performance material in the midst of its digitalization. ML is nowadays a pervasive technology with plenty of possible applications for an innovative industrial player. But what differentiates a successful project from a failing one? How can a researcher extract value from data instead of using valuable resources to generate data?
This talk aims at giving you an idea of some of the main applications of ML currently active at CERATIZIT and some tips to make your next industrial partnership a success.
Additional material: