Prediction Framework
Prediction frameworks leverage machine learning and deep learning to forecast future states across diverse domains, aiming to improve decision-making and resource allocation. Current research emphasizes the development of robust models, including deep convolutional neural networks, recurrent networks, and generative models, often incorporating techniques like transfer learning and explainable AI to enhance accuracy and interpretability. These frameworks find applications in various fields, from healthcare diagnostics and autonomous driving to energy management and social media analytics, offering significant potential for optimizing resource utilization and improving the efficiency of complex systems.
Papers
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