Apprendre à apprendre: amélioration des stratégies de travail et d'apprentissage à l'école by David Vuffray

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Learning as filtering: Implications for spike-based plasticity. by Jannes Jegminat, Simone Carlo Surace, Jean-Pascal Pfister

“…Most normative models in computational neuroscience describe the task of learning as the optimisation of a cost function with respect to a set of parameters. …”
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Advances in Machine Learning for Mechanically Ventilated Patients by Xu Y, Xue J, Deng Y, Tu L, Ding Y, Zhang Y, Yuan X, Xu K, Guo L, Gao N

“…ML can optimize patient management, improving clinical decisions, patient outcomes, and resource use.Objective: This review aims to summarize the current applications, challenges, and future directions of machine learning in managing mechanically ventilated patients, focusing on prediction models for extubation readiness, oxygenation management, ventilator parameter optimization, clinical prognosis, and pulmonary function assessment.Methods: Multiple databases, including PubMed, Web of Science, CNKI and Wanfang Data were systematically searched for studies on machine learning in mechanical ventilation management. …”
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Phygital learning ecosystems and places beyond 2030 by Carlo Giovannella, Giuseppe Roccasalva

“…Finally the cultural paradigm (people in place centred design), the pedagogical framework of reference (learning by being) and the didactic approach (P3BL: problem-project-process based learning) that should serve as a source of inspiration for the design of future learning places, and/or for the renovation of existing ones, are discussed. …”
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Generative learning of continuous data by tensor networks by Alex Meiburg, Jing Chen, Jacob Miller, Raphaëlle Tihon, Guillaume Rabusseau, Alejandro Perdomo-Ortiz

“…We develop our method in the setting of matrix product states, first deriving a universal expressivity theorem proving the ability of this model family to approximate any reasonably smooth probability density function with arbitrary precision. We then benchmark the performance of this model on several synthetic and real-world datasets, finding that the model learns and generalizes well on distributions of continuous and discrete variables. …”
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Statistical learning dynamically shapes auditory perception by Sahil Luthra, Austin Luor, Adam T. Tierney, Frederic Dick, Lori L. Holt

“…A novel bias emerges as well: lower frequencies are perceived as longer and higher ones as shorter. Probability-driven learning dynamically shapes perception, driven by interacting influences of sensory processing, distributional learning, and selective attention that sculpt a gain function involving modest enhancement of more-likely stimuli, and robust suppression of less-likely stimuli.…”
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The cerebellum is involved in implicit motor sequence learning by Mahyar Firouzi, Mahyar Firouzi, Mahyar Firouzi, Mahyar Firouzi, Kris Baetens, Kris Baetens, Catalina Duta, Catalina Duta, Chris Baeken, Chris Baeken, Chris Baeken, Frank Van Overwalle, Frank Van Overwalle, Eva Swinnen, Eva Swinnen, Eva Swinnen, Natacha Deroost, Natacha Deroost

“…BackgroundImplicit motor sequence learning (IMSL) is a cognitive function that allows us to execute multiple movements in a specific sequential order and plays a crucial role in our daily functional activities. …”
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Kurdish Language Learning Tool in Serious Game by Gulala Ali Hama Amin, Karzan Hussein Sharif

“…Hence smartphone devices become user-friendly and necessary tools in every individuals’ life, as it is a multi-function device. In this paper we designed and implemented a smartphone application to learn the Kurdish language and improve vocabulary via a serious game. …”
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Computational analysis of learning in young and ageing brains by Jayani Hewavitharana, Kathleen Steinhofel, Karl Peter Giese, Carolina Moretti Ierardi, Amida Anand

“…Although there are numerous studies on computational models and approaches which aim to mimic the learning process of the brain, they often concentrate on generic neural function exhibiting the potential need for models that address age-related changes in learning. …”
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Quantum Kernel Machine Learning With Continuous Variables by Laura J. Henderson, Rishi Goel, Sally Shrapnel

“…The popular qubit framework has dominated recent work on quantum kernel machine learning, with results characterising expressivity, learnability and generalisation. …”
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Distributionally Robust Policy and Lyapunov-Certificate Learning by Kehan Long, Jorge Cortes, Nikolay Atanasov

“…We integrate this condition into a loss function for training a neural network-based controller and show that, for the resulting closed-loop system, the global asymptotic stability of its equilibrium can be certified with high confidence, even with Out-of-Distribution (OoD) model uncertainties. …”
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On learning higher-order cumulants in diffusion models by Gert Aarts, Diaa E Habibi, Lingxiao Wang, Kai Zhou

“…To analyse how diffusion models learn correlations beyond Gaussian ones, we study the behaviour of higher-order cumulants, or connected n -point functions, under both the forward and backward process. …”
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Application of machine learning to growth model in fisheries by Semra Benzer, Recep Benzer, Ali Gül

“… Traditional growth models, such as length-weight relationships (LWRs) and the von Bertalanffy (VB) growth function, have been widely used in fishery science. …”
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Evolutionary learning in neural networks by heterosynaptic plasticity by Zedong Bi, Ruiqi Fu, Guozhang Chen, Dongping Yang, Yu Zhou, Liang Tian

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Advances in Corneal Diagnostics Using Machine Learning by Noor T. Al-Sharify, Salman Yussof, Nebras H. Ghaeb, Zainab T. Al-Sharify, Husam Yahya Naser, Sura M. Ahmed, Ong Hang See, Leong Yeng Weng

“…This paper explores the cornea’s function in maintaining ocular health, detailing its anatomy, pathological conditions, and the latest developments in diagnostic techniques. …”
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Model-Based AUV Path Planning Using Curriculum Learning and Deep Reinforcement Learning on a Simplified Electronic Navigation Chart by Łukasz Marchel, Rafał Kot, Piotr Szymak, Paweł Piskur

“…Deep Reinforcement Learning (DRL)-based algorithms have demonstrated substantial effectiveness in tackling complex control problems for autonomous underwater vehicles (AUVs). …”
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Integrated Learning Models for Micro-Teaching Course by Jusuf Blegur, Amung Ma'mun, . Berliana, Agus Mahendra, Muhammad Nur Alif, Tite Juliantine, Andreas J. F. Lumba

“…Thus, the 25-task performance in the integrated learning model has a significant psychometric function relative to the actual situation, so it becomes one of the references that lecturers can use to improve the competency of prospective teachers in micro-teaching courses (not limited to teaching skills, analytical thinking skills, academic integrity, and transformational leadership).   …”
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Role of Songs when Teaching English within Inclusive Education by I. S. Samokhin, N. L. Sokolova, E. A. Mrachenko, M. G. Sergeyeva, M. V. Mishatkina

“…The relevance of the chosen topic is determined by the implementation of the Federal law “On education in Russian Federation,” providing the use of inclusive techniques and technologies in learning and education. The novelty of the research is seen in the fact that a hedonic function of the educational environment is recognized not only as supporting the educational one, but also valuable in itself, having independent significance. …”
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A novel committee machine and reviews of neural network and statistical models for currency exchange rate prediction: An experimental analysis by Trilok Nath Pandey, Alok Kumar Jagadev, Satchidananda Dehuri, Sung-Bae Cho

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Differential modulation of the cortical alpha rhythm and activation of distinct neural networks during tactile perception training by learners and non-learners by Kei Saito, Kei Saito, Naofumi Otsuru, Naofumi Otsuru, Kaito Tateishi, Ryuji Kurebayashi, Hideaki Onishi, Hideaki Onishi

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