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Multiscale Thermomechanical Simulations of 3D Printed Materials using Deep Learning

• Authors : Radermecker, Arnaud; A&M - Aérospatiale et Mécanique - ULiège

Subjects: Finite element squared; multiscale simulations; deep learning

• Source: SPACE4RELAUCNH PhD Day, Bruxelles, Belgium [BE], 07/02/2025

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Using Deep Convolutional Neural Networks to Model Face Learning

• Authors : Legrand, Raphaël; Defays, Daniel; Sougné, Jacques

Subjects: Face learning; Face recognition; deep learning

• Source: Annual Meeting of the Belgian Association for Psychological Sciences, Brussels, Belgium [BE], 31-05-2024

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Multiscale Thermomechanical Simulations of 3D Printed Materials using Deep Learning

• Authors : Radermecker, Arnaud

Subjects: deep learning; numerical simulation; finite element square

• Source: SPACE4RELAUCNH PhD Day, Louvain-La-neuve, Belgium [BE], 07/02/2024

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Will artificial intelligence revolutionize aerial surveys? A first large-scale semi-automated survey of African wildlife using oblique imagery and deep learning

• Authors : Delplanque, Alexandre; Linchant, Julie; Vincke, Xavier

Subjects: aerial survey; deep learning; wildlife

• Source: Ecological Informatics, 82, 102679 (2024-06)

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Strategic learning of people's names as a function of expected utility in young and older adults.

• Authors : Devue, Christel; Badolle, Marie; Brédart, Serge

Subjects: Aging; cost-efficiency; learning

• Source: Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, 1 - 17 (2024-03-29)

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Multi-Context Point Cloud Dataset and Machine Learning for Railway Semantic Segmentation ; Ensemble de données de nuages de points multi-contexte et apprentissage automatique pour la segmentation sémantique des chemins de fer

• Authors : Kharroubi, Abderrazzaq; Ballouch, Zouhair; Hajji, Rafika

Subjects: railways; LiDAR; dataset

• Source: Infrastructures, 9 (4), 71 (2024-04-09)

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Optimal control of renewable energy communities subject to network peak fees with model predictive control and reinforcement learning algorithms

• Authors : Aittahar, Samy; Bolland, Adrien; Derval, Guillaume

Subjects: renewable energy communities; machine learning; reinforcement learning

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Vibrational properties of Molybdenum Sulphides at finite T combining ab initio methods and Machine Learning

• Authors : Longo, Samuel; Verstraete, Matthieu

Subjects: DFT; ab initio; phonons

• Source: Blending the DFT-Based Multiple Scattering Greens’ Function Approach to Spectroscopies with Machine Learning, Les Houches, France [FR], 30/10/2023-12/11/2023

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Reinforcement Learning to improve delta robot throws for sorting scrap metal

• Authors : Louette, Arthur; Lambrechts, Gaspard; Ernst, Damien ...

Subjects: Delta robot; reinforcement learning; PyBullet

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The Lockdown in Retrospect: An International, Mixed Methods Perspective on Student and Faculty Experiences with COVID-19 Remote Learning ; Le confinement dans le rétroviseur : une perspective internationale sur l'expérience des étudiants et des enseignants en matière d'apprentissage à distance dans le cadre du COVID-19

• Authors : Archibald, Audon; Heap, Tania; Lucke, Heather

Subjects: remote learning; confinement; lockdown

• Source: urn:isbn:978-3-03-125102-3 ; urn:isbn:978-3-03-125101-6 ; Reimagining Education: Studies and Stories for Effective Learning in an Evolving Digital Environment

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