60 citations · 215 across the 36 of their papers we have counts for
41 papers
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets
Vishnu Suresh Lokhande, Rudrasis Chakraborty, Sathya N. Ravi +1
Pooling multiple neuroimaging datasets across institutions often enables improvements in statistical power when evaluating associations (e.g., between risk factors and disease outc…
Graph Reparameterizations for Enabling 1000+ Monte Carlo Iterations in Bayesian Deep Neural Networks
Jurijs Nazarovs, Ronak R. Mehta, Vishnu Suresh Lokhande +1
Uncertainty estimation in deep models is essential in many real-world applications and has benefited from developments over the last several years. Recent evidence suggests that ex…
Mixed Effects Neural ODE: A Variational Approximation for Analyzing the Dynamics of Panel Data
Jurijs Nazarovs, Rudrasis Chakraborty, Songwong Tasneeyapant +2
Panel data involving longitudinal measurements of the same set of participants taken over multiple time points is common in studies to understand childhood development and disease…
Forward Operator Estimation in Generative Models with Kernel Transfer Operators
Zhichun Huang, Rudrasis Chakraborty, Vikas Singh
Generative models which use explicit density modeling (e.g., variational autoencoders, flow-based generative models) involve finding a mapping from a known distribution, e.g. Gauss…
You Only Sample (Almost) Once: Linear Cost Self-Attention Via Bernoulli Sampling
Zhanpeng Zeng, Yunyang Xiong, Sathya N. Ravi +3
Transformer-based models are widely used in natural language processing (NLP). Central to the transformer model is the self-attention mechanism, which captures the interactions of…
An Online Riemannian PCA for Stochastic Canonical Correlation Analysis
Zihang Meng, Rudrasis Chakraborty, Vikas Singh
We present an efficient stochastic algorithm (RSG+) for canonical correlation analysis (CCA) using a reparametrization of the projection matrices. We show how this reparametrizatio…