— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and ...
Alison A. Motsinger, Stephen L. Lee, George Mellic...
Spiking Neural Networks (SNNs) model the biological functions of the human brain enabling neuro/computer scientists to investigate how arrays of neurons can be used to solve comput...
Brendan P. Glackin, Jim Harkin, T. Martin McGinnit...
Advances in data collection technologies allow accumulation of large and high dimensional datasets and provide opportunities for learning high quality classification and regression...
Whilst conventional approach in structural design is based on reliability-calibrated factored design formula, performance-based design customizes a solution to the specific circum...