18 citations · 18 across the 2 of their papers we have counts for
4 papers · 1 filter
Manifold Regularization for Memory-Efficient Training of Deep Neural Networks
Shadi Sartipi, Edgar A. Bernal
One of the prevailing trends in the machine- and deep-learning community is to gravitate towards the use of increasingly larger models in order to keep pushing the state-of-the-art…
Training Deep Normalizing Flow Models in Highly Incomplete Data Scenarios with Prior Regularization
Edgar A. Bernal
Deep generative frameworks including GANs and normalizing flow models have proven successful at filling in missing values in partially observed data samples by effectively learning…
MCFlow: Monte Carlo Flow Models for Data Imputation
Trevor W. Richardson, Wencheng Wu, Lei Lin +2
We consider the topic of data imputation, a foundational task in machine learning that addresses issues with missing data. To that end, we propose MCFlow, a deep framework for impu…
Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis
Lei Lin, Beilei Xu, Wencheng Wu +2
Myotonia, which refers to delayed muscle relaxation after contraction, is the main symptom of myotonic dystrophy patients. We propose a hierarchical attention-based temporal convol…