We present a novel recurrent neural network (RNN)-based model that combines the remembering ability of unitary evolution RNNs with the ability of gated RNNs to effectively forget redundant or irrelevant information in its memory. We achieve this by e...
Neural networks : the official journal of the International Neural Network Society
Feb 1, 2019
Gaussian Processes (GPs) models have been successfully applied to the problem of learning from sequential observations. In such context, the family of Recurrent Gaussian Processes (RGPs) have been recently introduced with a specifically designed stru...
Our knowledge of events and situations in the world plays a critical role in our ability to understand what is happening around us, to predict what might happen next, and to comprehend language. What has not been so clear is the form and structure of...
Research in developmental disabilities
Jan 21, 2019
BACKGROUND: Individuals with autism spectrum disorder (ASD) tend to show deficits in engaging with humans. Previous findings have shown that robot-based training improves the gestural recognition and production of children with ASD. It is not known w...
The brain has the ability to flexibly perform many tasks, but the underlying mechanism cannot be elucidated in traditional experimental and modeling studies designed for one task at a time. Here, we trained single network models to perform 20 cogniti...
We consider the ancestral state reconstruction problem where we need to infer phenotypes of ancestors using observations from present-day species. For this problem, we propose a multi-task learning method that uses regularized maximum likelihood to e...
Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrated that anodal tDCS and high-definition (HD) tDCS of the motor cortex can enhance motor skill acquisition in children, but behavioral mechanisms remai...
Computational intelligence and neuroscience
Dec 10, 2018
In this research article, we study the problem of employing a neural machine translation model to translate Arabic dialects to modern standard Arabic. The proposed solution of the neural machine translation model is prompted by the recurrent neural n...
Computational intelligence and neuroscience
Dec 6, 2018
Multiple-input and multiple-output (MIMO) technology is one of the latest technologies to enhance the capacity of the channel as well as the service quality of the communication system. By using the MIMO technology at the physical layer, the estimati...
Neural networks : the official journal of the International Neural Network Society
Nov 27, 2018
Traditional Turing Machines (TMs) are symbolic whose hand-crafted representations are static and limited. Developmental Network 1 (DN-1) uses emergent representation to perform Turing Computation. But DN-1 lacks hierarchy in its internal representati...