In this paper we study neural networks and their approximating power in panel data models. We provide asymptotic guarantees on deep feed-forward neural network estimation of the conditional mean, ...
Neural network approximation techniques have emerged as a formidable approach in computational mathematics and machine learning, providing robust tools for approximating complex functions. By ...
“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
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New framework for predicting TAIs in hydrogen combustion
Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving real-time monitoring and combustion safety.
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