Satya Narayan Shukla

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University of Massachusetts Amherst

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∙ 07/23/2021

Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series

Irregularly sampled time series commonly occur in several domains where ...

Satya Narayan Shukla, et al. ∙

∙ 01/25/2021

Multi-Time Attention Networks for Irregularly Sampled Time Series

Irregular sampling occurs in many time series modeling applications wher...

Satya Narayan Shukla, et al. ∙

∙ 11/30/2020

A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance

Irregularly sampled time series data arise naturally in many application...

Satya Narayan Shukla, et al. ∙

∙ 10/08/2020

Gaussian MRF Covariance Modeling for Efficient Black-Box Adversarial Attacks

We study the problem of generating adversarial examples in a black-box s...

Anit Kumar Sahu, et al. ∙

∙ 07/13/2020

Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes

We focus on the problem of black-box adversarial attacks, where the aim ...

Satya Narayan Shukla, et al. ∙

∙ 03/24/2020

Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction

Intensive Care Unit Electronic Health Records (ICU EHRs) store multimoda...

Satya Narayan Shukla, et al. ∙

∙ 02/07/2020

Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification

In this paper, we consider the problem of assessing the adversarial robu...

Meet P. Vadera, et al. ∙

∙ 09/30/2019

Black-box Adversarial Attacks with Bayesian Optimization

We focus on the problem of black-box adversarial attacks, where the aim ...

Satya Narayan Shukla, et al. ∙

∙ 09/13/2019

Interpolation-Prediction Networks for Irregularly Sampled Time Series

In this paper, we present a new deep learning architecture for addressin...

Satya Narayan Shukla, et al. ∙

∙ 12/03/2018

Modeling Irregularly Sampled Clinical Time Series

While the volume of electronic health records (EHR) data continues to gr...

Satya Narayan Shukla, et al. ∙