23 citations · 53 across the 4 of their papers we have counts for
4 papers
Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
T. Barfoot, J. Burgner-Kahrs, E. Diller +12
From disinfection and remote triage, to logistics and delivery, countries around the world are making use of robots to address the unique challenges presented by the COVID-19 pande…
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data
Matthew B. A. McDermott, Bret Nestor, Evan Kim +4
Multi-task learning (MTL) is a machine learning technique aiming to improve model performance by leveraging information across many tasks. It has been used extensively on various d…
Using Generative Models for Pediatric wbMRI
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu +3
Early detection of cancer is key to a good prognosis and requires frequent testing, especially in pediatrics. Whole-body magnetic resonance imaging (wbMRI) is an essential part of…
Dr.VAE: Drug Response Variational Autoencoder
Ladislav Rampasek, Daniel Hidru, Petr Smirnov +2
We present two deep generative models based on Variational Autoencoders to improve the accuracy of drug response prediction. Our models, Perturbation Variational Autoencoder and it…