papers

Publications (9)

math.GR2026

Spectral properties of the Schreier graphs of the basilica group

Kyle Ambrose, Noah Dunham, Michael Morris +2

We study the spectral properties of Laplacians on the Schreier graphs of the basilica group, the iterated monodromy group of the polynomial , which is an important…

eess.IV2021

Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network

Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay +7

We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated a…

cs.LG2020

Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening

Sumeet Menon, David Chapman, Phuong Nguyen +3

We present a semi-supervised algorithm for lung cancer screening in which a 3D Convolutional Neural Network (CNN) is trained using the Expectation-Maximization (EM) meta-algorithm.…

cs.LG2024

Forecasting infectious disease prevalence with associated uncertainty using neural networks

Michael Morris

Infectious diseases pose significant human and economic burdens. Accurately forecasting disease incidence can enable public health agencies to respond effectively to existing or em…

math.CO2023

On colouring oriented graphs of large girth

P. Mark Kayll, Michael Morris

We prove that for every oriented graph and every choice of positive integers and , there exists an oriented graph along with a surjective homomorphism $ψ\colon…

cs.LG2020

Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN

Sumeet Menon, Joshua Galita, David Chapman +7

COVID-19 is a novel infectious disease responsible for over 800K deaths worldwide as of August 2020. The need for rapid testing is a high priority and alternative testing strategie…

cs.LG2024

The Impact of an XAI-Augmented Approach on Binary Classification with Scarce Data

Ximing Wen, Rosina O. Weber, Anik Sen +9

Point-of-Care Ultrasound (POCUS) is the practice of clinicians conducting and interpreting ultrasound scans right at the patient's bedside. However, the expertise needed to interpr…

cs.LG2021

Estimating the Uncertainty of Neural Network Forecasts for Influenza Prevalence Using Web Search Activity

Michael Morris, Peter Hayes, Ingemar J. Cox +1

Influenza is an infectious disease with the potential to become a pandemic, and hence, forecasting its prevalence is an important undertaking for planning an effective response. Re…

eess.IV2021

CCS-GAN: COVID-19 CT-scan classification with very few positive training images

Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita +7

We present a novel algorithm that is able to classify COVID-19 pneumonia from CT Scan slices using a very small sample of training images exhibiting COVID-19 pneumonia in tandem wi…