Temporal Neural Network

Temporal Neural Networks (TNNs) are a class of spiking neural networks designed to efficiently process temporal data, mirroring aspects of biological neural processing. Current research focuses on improving TNN architectures for various applications, including video processing (e.g., super-resolution), time series forecasting (addressing non-stationarity), and neuromorphic computing (optimizing hardware implementations for energy efficiency). These advancements are driving progress in diverse fields, from medical image analysis and industrial process monitoring to music tagging and human motion prediction, demonstrating the broad applicability and impact of TNNs.