Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Introduction: The COVID-19 pandemic accelerated global online education, which faces “shallow learning” challenges. Deep learning is key to student competencies. Based on sociocultural theory, this ...
Objective: Construct a predictive model for rehabilitation outcomes in ischemic stroke patients 3 months post-stroke using resting state functional magnetic resonance imaging (fMRI) images, as well as ...
Abstract: The integration of wind power into microgrids significantly increases the complexity of the microgrid’s dynamical behavior and introduces higher levels of uncertainty. This paper addresses ...
Official implementation of the SAM-GS optimizer for multitask learning ArxIv Comparison of different MTL methods for 20000 steps.\ Top row: The loss trajectories of different MTL methods in the loss ...
Tristan Jurkovich began his career as a journalist in 2011. His childhood love of video games and writing fuel his passion for archiving this great medium’s history. He dabbles in every genre, but ...
Abstract: For satellite brightness temperature images, researchers are constantly pursuing higher resolutions to obtain more detailed meteorological information. In this paper, a novel ...
This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis. The ...
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