activity
20182020
most citedOptimal Scheduling of Anticipated COVID-19 Vaccination: A Case Study of New York State

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

q-bio.PE20202 cited

Optimal Scheduling of Anticipated COVID-19 Vaccination: A Case Study of New York State

Syed Irfan Ali Meerza, Seyed M. Karimi, Bert B. Little +2

This study aims to determine an optimal control strategy for vaccine scheduling in COVID-19 pandemic treatment by converting widely acknowledged infectious disease model named SEIR…

cs.LG2019

On Correlation of Features Extracted by Deep Neural Networks

Babajide O. Ayinde, Tamer Inanc, Jacek M. Zurada

Redundancy in deep neural network (DNN) models has always been one of their most intriguing and important properties. DNNs have been shown to overparameterize, or extract a lot of…

cs.LG2019

Diversity Regularized Adversarial Learning

Babajide O. Ayinde, Keishin Nishihama, Jacek M. Zurada

The two key players in Generative Adversarial Networks (GANs), the discriminator and generator, are usually parameterized as deep neural networks (DNNs). On many generative tasks,…

cs.CV2018

Building Efficient ConvNets using Redundant Feature Pruning

Babajide O. Ayinde, Jacek M. Zurada

This paper presents an efficient technique to prune deep and/or wide convolutional neural network models by eliminating redundant features (or filters). Previous studies have shown…

cs.LG2018

Deep Learning of Nonnegativity-Constrained Autoencoders for Enhanced Understanding of Data

Babajide O. Ayinde, Jacek M. Zurada

Unsupervised feature extractors are known to perform an efficient and discriminative representation of data. Insight into the mappings they perform and human ability to understand…