From industrial robots to self-driving cars, engineers face a common problem: keeping machines steady and predictable. When ...
BiGRU, a deep learning model that enhances data recovery in structural health monitoring, ensuring the reliability of bridge ...
The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...
A research group from the University of Osaka, Zen University, and the University of Tokyo has mathematically uncovered the ...
By enhancing forecast precision, the system enables governments to preempt budgetary imbalances, reduce waste, and optimize spending efficiency. The authors argue that the combination of machine ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network (QCNN) based on hybrid quantum-classical learning and ...
The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic of theirs. An ANN is a machine learning model. Like all machine learning ...
A new study reveals that hovering can be controlled by simple feedback, challenging previous theories of complex neural ...
The nature of dark matter remains one of the greatest mysteries in cosmology. Within the standard framework of ...
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