13 citations · 49 across the 60 of their papers we have counts for
5 papers · 1 filter
DeConFuse : A Deep Convolutional Transform based Unsupervised Fusion Framework
Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2
This work proposes an unsupervised fusion framework based on deep convolutional transform learning. The great learning ability of convolutional filters for data analysis is well ac…
ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis
Pooja Gupta, Jyoti Maggu, Angshul Majumdar +2
This work addresses the problem of analyzing multi-channel time series data %. In this paper, we by proposing an unsupervised fusion framework based on %the recently proposed convo…
Deep Convolutional Transform Learning -- Extended version
Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux +1
This work introduces a new unsupervised representation learning technique called Deep Convolutional Transform Learning (DCTL). By stacking convolutional transforms, our approach is…
DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19
Aanchal Mongia, Stuti Jain, Emilie Chouzenoux +1
This work formulates antiviral repositioning as a matrix completion problem where the antiviral drugs are along the rows and the viruses along the columns. The input matrix is part…
A computational approach to aid clinicians in selecting anti-viral drugs for COVID-19 trials
Aanchal Mongia, Sanjay Kr. Saha, Emilie Chouzenoux +1
COVID-19 has fast-paced drug re-positioning for its treatment. This work builds computational models for the same. The aim is to assist clinicians with a tool for selecting prospec…