84 citations · 234 across the 23 of their papers we have counts for
26 papers
Independence Properties of Generalized Submodular Information Measures
Himanshu Asnani, Jeff Bilmes, Rishabh Iyer
Recently a class of generalized information measures was defined on sets of items parametrized by submodular functions. In this paper, we propose and study various notions of indep…
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…
MaskAAE: Latent space optimization for Adversarial Auto-Encoders
Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran +3
The field of neural generative models is dominated by the highly successful Generative Adversarial Networks (GANs) despite their challenges, such as training instability and mode c…