research
∙
12/16/2022
Toward Improved Generalization: Meta Transfer of Self-supervised Knowledge on Graphs
Despite the remarkable success achieved by graph convolutional networks ...
share
research
∙
12/03/2022
Semi-supervised Learning with Robust Loss in Brain Segmentation
In this work, we used a semi-supervised learning method to train deep le...
research
∙
08/08/2022
Learning from imperfect training data using a robust loss function: application to brain image segmentation
Segmentation is one of the most important tasks in MRI medical image ana...
research
∙
03/03/2022
Semi-supervised Learning using Robust Loss
The amount of manually labeled data is limited in medical applications, ...
research
∙
12/13/2020
fMRI-Kernel Regression: A Kernel-based Method for Pointwise Statistical Analysis of rs-fMRI for Population Studies
Due to the spontaneous nature of resting-state fMRI (rs-fMRI) signals, c...
research
∙
10/18/2020
Addressing Variance Shrinkage in Variational Autoencoders using Quantile Regression
Estimation of uncertainty in deep learning models is of vital importance...
research
∙
06/15/2020
Robust Variational Autoencoder for Tabular Data with Beta Divergence
We propose a robust variational autoencoder with β divergence for tabula...
research
∙
05/23/2019