Abstract For the goal of automated design high-performance deep convolutional neural networks (CNNs), architecture search (NAS) methodology is becoming increasingly important for both academia and industries. Due to costly stochastic gradient descent training CNNs performance evaluation, most existing NAS methods are computationally expensive real-world deployments. To address this issue, we fi...

This review addresses issues of various drift–diffusion and inhomogeneous advection problems with without resetting on comblike structures. Both a Brownian diffusion search drift an the comb structures are analyzed. The analytical results verified by numerical simulations in terms coupled Langevin equations for structure. subordination approach is one main technical methods used here, we demons...