Prediction Network

Prediction networks are artificial neural networks designed to forecast future states or values based on past data, aiming to improve accuracy and efficiency across diverse applications. Current research emphasizes developing sophisticated architectures, such as those incorporating graph convolutional networks, recurrent networks, and attention mechanisms, to effectively capture complex spatiotemporal correlations in multivariate time series and high-dimensional data. These advancements are impacting fields ranging from weather forecasting and anomaly detection to human motion prediction and resource-efficient model deployment in decentralized environments. The ultimate goal is to create more accurate, robust, and resource-conscious predictive models for a wide array of scientific and practical problems.