6 citations · 14 across the 17 of their papers we have counts for
5 papers · 1 filter
Visualization of topology optimization designs with representative subset selection
Daniel J Perry, Vahid Keshavarzzadeh, Shireen Y Elhabian +3
An important new trend in additive manufacturing is the use of optimization to automatically design industrial objects, such as beams, rudders or wings. Topology optimization, as i…
GENs: Generative Encoding Networks
Surojit Saha, Shireen Elhabian, Ross T. Whitaker
Mapping data from and/or onto a known family of distributions has become an important topic in machine learning and data analysis. Deep generative models (e.g., generative adversar…
Unsupervised Shape Normality Metric for Severity Quantification
Wenzheng Tao, Riddhish Bhalodia, Erin Anstadt +3
This work describes an unsupervised method to objectively quantify the abnormality of general anatomical shapes. The severity of an anatomical deformity often serves as a determina…
Self-Supervised Discovery of Anatomical Shape Landmarks
Riddhish Bhalodia, Ladislav Kavan, Ross Whitaker
Statistical shape analysis is a very useful tool in a wide range of medical and biological applications. However, it typically relies on the ability to produce a relatively small n…
Workshop on Quantification, Communication, and Interpretation of Uncertainty in Simulation and Data Science
Ross Whitaker, William Thompson, James Berger +7
Modern science, technology, and politics are all permeated by data that comes from people, measurements, or computational processes. While this data is often incomplete, corrupt, o…