18 citations · 34 across the 8 of their papers we have counts for
6 papers · 1 filter
Filling out the missing gaps: Time Series Imputation with Semi-Supervised Learning
Karan Aggarwal, Jaideep Srivastava
Missing data in time series is a challenging issue affecting time series analysis. Missing data occurs due to problems like data drops or sensor malfunctioning. Imputation methods…
Embarrassingly Simple MixUp for Time-series
Karan Aggarwal, Jaideep Srivastava
Labeling time series data is an expensive task because of domain expertise and dynamic nature of the data. Hence, we often have to deal with limited labeled data settings. Data aug…
Benchmarking Regression Methods: A comparison with CGAN
Karan Aggarwal, Matthieu Kirchmeyer, Pranjul Yadav +2
In recent years, impressive progress has been made in the design of implicit probabilistic models via Generative Adversarial Networks (GAN) and its extension, the Conditional GAN (…
Two Birds with One Network: Unifying Failure Event Prediction and Time-to-failure Modeling
Karan Aggarwal, Onur Atan, Ahmed Farahat +3
One of the key challenges in predictive maintenance is to predict the impending downtime of an equipment with a reasonable prediction horizon so that countermeasures can be put in…
Adversarial Unsupervised Representation Learning for Activity Time-Series
Karan Aggarwal, Shafiq Joty, Luis Fernandez-Luque +1
Sufficient physical activity and restful sleep play a major role in the prevention and cure of many chronic conditions. Being able to proactively screen and monitor such chronic co…
Co-Morbidity Exploration on Wearables Activity Data Using Unsupervised Pre-training and Multi-Task Learning
Karan Aggarwal, Shafiq Joty, Luis F. Luque +1
Physical activity and sleep play a major role in the prevention and management of many chronic conditions. It is not a trivial task to understand their impact on chronic conditions…