84 citations · 234 across the 23 of their papers we have counts for
6 papers · 1 filter
ScRAE: Deterministic Regularized Autoencoders with Flexible Priors for Clustering Single-cell Gene Expression Data
Arnab Kumar Mondal, Himanshu Asnani, Parag Singla +1
Clustering single-cell RNA sequence (scRNA-seq) data poses statistical and computational challenges due to their high-dimensionality and data-sparsity, also known as `dropout' even…
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures
Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan +3
We study submodular information measures as a rich framework for generic, query-focused, privacy sensitive, and update summarization tasks. While past work generally treats these p…
To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs
Arnab Kumar Mondal, Himanshu Asnani, Parag Singla +1
Regularized Auto-Encoders (RAEs) form a rich class of neural generative models. They effectively model the joint-distribution between the data and the latent space using an Encoder…
C-MI-GAN : Estimation of Conditional Mutual Information using MinMax formulation
Arnab Kumar Mondal, Arnab Bhattacharya, Sudipto Mukherjee +3
Estimation of information theoretic quantities such as mutual information and its conditional variant has drawn interest in recent times owing to their multifaceted applications. N…
CCMI : Classifier based Conditional Mutual Information Estimation
Sudipto Mukherjee, Himanshu Asnani, Sreeram Kannan
Conditional Mutual Information (CMI) is a measure of conditional dependence between random variables X and Y, given another random variable Z. It can be used to quantify conditiona…
ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
Sudipto Mukherjee, Himanshu Asnani, Eugene Lin +1
Generative Adversarial networks (GANs) have obtained remarkable success in many unsupervised learning tasks and unarguably, clustering is an important unsupervised learning problem…