Neural networks : the official journal of the International Neural Network Society
Jun 2, 2021
Graph convolutional networks (GCNs) have been widely used for representation learning on graph data, which can capture structural patterns on a graph via specifically designed convolution and readout operations. In many graph classification applicati...
Assistive technology : the official journal of RESNA
May 28, 2021
Socially assistive robots (SAR) have the potential to impact therapies for Autism Spectrum Disorder (ASD) by supporting clinicians in increasing learning opportunities presented to individuals. Recent research on robot-mediated intervention (RMI) del...
. Both artificial and biological controllers experience errors during learning that are probabilistically distributed. We develop a framework for modeling distributions of errors and relating deviations in these distributions to neural activity.. The...
Learning styles are critical to educational psychology, especially when investigating various contextual factors that interact with individual learning styles. Drawing upon Biglan's taxonomy of academic tribes, this study systematically analyzed the ...
Computational intelligence and neuroscience
May 17, 2021
Particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search technique used to search for food with the intrinsic manner of bee swarming. PSO is widely used to solve the diverse problems of optimization. Initializat...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 15, 2021
Training deep ConvNets requires large labeled datasets. However, collecting pixel-level labels for medical image segmentation is very expensive and requires a high level of expertise. In addition, most existing segmentation masks provided by clinical...
Neural networks : the official journal of the International Neural Network Society
May 14, 2021
We introduce the novel concept of anti-transfer learning for speech processing with convolutional neural networks. While transfer learning assumes that the learning process for a target task will benefit from re-using representations learned for anot...
Increases in the scale and complexity of behavioral data pose an increasing challenge for data analysis. A common strategy involves replacing entire behaviors with small numbers of handpicked, domain-specific features, but this approach suffers from ...
Synaptic plasticity is believed to be a key physiological mechanism for learning. It is well established that it depends on pre- and postsynaptic activity. However, models that rely solely on pre- and postsynaptic activity for synaptic changes have, ...
Neural networks : the official journal of the International Neural Network Society
May 12, 2021
Motivated by biological considerations, we study sparse neural maps from an input layer to a target layer with sparse activity, and specifically the problem of storing K input-target associations (x,y), or memories, when the target vectors y are spar...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.