Results 81 to 90 of about 8,331,707 (294)

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source

Multiagent Deep Reinforcement Learning Algorithms in StarCraft II: A Review

IEEE Access
StarCraft II, as a real-time strategy game, features multiagent collaboration, complex decision-making processes, partially observable environments, and long-term credit assignment; thus, it is an ideal platform for exploring, validating, and optimizing ...
Yanyan Li, Yijun Wang, Yiwei Zhou
doaj   +1 more source

BoxStacker: Deep Reinforcement Learning for 3D Bin Packing Problem in Virtual Environment of Logistics Systems

Sensors, 2023
Manufacturing systems need to be resilient and self-organizing to adapt to unexpected disruptions, such as product changes or rapid order, in supply chain changes while increasing the automation level of robotized logistics processes to cope with the ...
Shokhikha Amalana Murdivien, Jumyung Um
doaj   +1 more source

Quantitative MRI Uncovers Subtle Cortical Damage in Myelin Oligodendrocyte Glycoprotein Antibody‐Associated Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether myelin‐sensitive quantitative MRI reveals microstructural abnormalities in normal‐appearing cortex (NACtx) in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), indicating that conventional MRI underestimates remission residual cortical injury.
Valentina Camera, Agnese Tamanti, Silvia Messina, Nicola Dall'Osto, Teresa Maltempo, Stefano Ziccardi, Matteo Foschi, Maria Grazia Piscaglia, Diana Ferraro, Francesco Crescenzo, Francesca Rossi, Albulena Bajrami, Sabrina Marangoni, Damiano Marastoni, Francesca Benedetta Pizzini, Maria Isabel Leite, Roberta Magliozzi, Patrick Waters, Massimiliano Calabrese, Jacqueline Palace, Ruth Geraldes   +20 more
wiley   +1 more source

LFDC: Low-Energy Federated Deep Reinforcement Learning for Caching Mechanism in Cloud–Edge Collaborative

Applied Sciences, 2023
The optimization of caching mechanisms has long been a crucial research focus in cloud–edge collaborative environments. Effective caching strategies can substantially enhance user experience quality in these settings.
Xinyu Zhang, Zhigang Hu, Meiguang Zheng, Yang Liang, Hui Xiao, Hao Zheng, Aikun Xu   +6 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Deep Successor Reinforcement Learning

CoRR, 2016
Learning robust value functions given raw observations and rewards is now possible with model-free and model-based deep reinforcement learning algorithms. There is a third alternative, called Successor Representations (SR), which decomposes the value function into two components -- a reward predictor and a successor map.
Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman   +3 more
openaire   +2 more sources

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source

Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Idiopathic hypersomnia (IH) presents with excessive daytime sleepiness (EDS) despite apparently preserved nocturnal sleep, challenging traditional models of hypersomnolence based on sleep loss or fragmentation. We aimed to test the hypothesis that EDS in IH reflects excessive stabilization of the sleep state, consistent with ...
Samantha Mombelli, Karine Lacourse, Hélène Blais, Anne‐Sophie Deshaies‐Rugama, Cynthia Thompson, Alex Desautels, Jacques Montplaisir, Milan Nigam, Christophe Moderie, Boshra Khajehpiri, Catherine Duclos, Jean Marc Lina, Julie Carrier, Nadia Gosselin   +13 more
wiley   +1 more source

Collaborative Deep Reinforcement Learning

CoRR, 2017
Besides independent learning, human learning process is highly improved by summarizing what has been learned, communicating it with peers, and subsequently fusing knowledge from different sources to assist the current learning goal. This collaborative learning procedure ensures that the knowledge is shared, continuously refined, and concluded from ...
Kaixiang Lin, Shu Wang, Jiayu Zhou
openaire   +3 more sources