research
∙
02/21/2021
Learning Deep Features for Shape Correspondence with Domain Invariance
Correspondence-based shape models are key to various medical imaging app...
share
research
∙
12/29/2020
Visualization of topology optimization designs with representative subset selection
An important new trend in additive manufacturing is the use of optimizat...
research
∙
10/28/2020
GENs: Generative Encoding Networks
Mapping data from and/or onto a known family of distributions has become...
research
∙
07/18/2020
Unsupervised Shape Normality Metric for Severity Quantification
This work describes an unsupervised method to objectively quantify the a...
research
∙
08/16/2019
A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration
Spatial transformations are enablers in a variety of medical image analy...
research
∙
08/16/2019
A Cooperative Autoencoder for Population-BasedRegularization of CNN Image Registration
Spatial transformations are enablers in a variety of medical image analy...
research
∙
12/30/2018
Allocation strategies for high fidelity models in the multifidelity regime
We propose a novel approach to allocating resources for expensive simula...
research
∙
09/28/2018
DeepSSM: A Deep Learning Framework for Statistical Shape Modeling from Raw Images
Statistical shape modeling is an important tool to characterize variatio...
research
∙
05/06/2018
Clustering With Pairwise Relationships: A Generative Approach
Semi-supervised learning (SSL) has become important in current data anal...
research
∙
10/08/2017
Exploration of Heterogeneous Data Using Robust Similarity
Heterogeneous data pose serious challenges to data analysis tasks, inclu...
research
∙
09/04/2017