Abstract: In the post-Moore era, heterogeneous integrated systems—such as chiplet-based designs—exhibit increasingly complex functional interface interconnections, demanding scalable and accurate ...
Abstract: In this brief, we investigate the approximation theory (AT) of Bayesian recurrent neural network (BRNN) for stochastic time series forecasting (TSF) from a probabilistic standpoint. Due to ...