30 citations · 75 across the 14 of their papers we have counts for
3 papers · 1 filter
Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression
Haleh Akrami, Anand A. Joshi, Sergul Aydore +1
Estimation of uncertainty in deep learning models is of vital importance, especially in medical imaging, where reliance on inference without taking into account uncertainty could l…
Robust Variational Autoencoder for Tabular Data with Beta Divergence
Haleh Akrami, Sergul Aydore, Richard M. Leahy +1
We propose a robust variational autoencoder with divergence for tabular data (RTVAE) with mixed categorical and continuous features. Variational autoencoders (VAE) and their va…
DropCluster: A structured dropout for convolutional networks
Liyan Chen, Philippos Mordohai, Sergul Aydore
Dropout as a common regularizer to prevent overfitting in deep neural networks has been less effective in convolutional layers than in fully connected layers. This is because Dropo…