Machine-Learned HASDM Model with Uncertainty Quantification

no code implementations • 16 Sep 2021 • Richard J. Licata, Piyush M. Mehta, W. Kent Tobiska, S. Huzurbazar

These models leverage Monte Carlo (MC) dropout to provide uncertainty estimates, and the use of the NLPD loss function results in well-calibrated uncertainty estimates without sacrificing model accuracy (<10% mean absolute error).

Dimensionality Reduction Uncertainty Quantification

A landmark-based algorithm for automatic pattern recognition and abnormality detection

no code implementations • 17 Feb 2016 • S. Huzurbazar, Long Lee, Dongyang Kuang

For illustration, we apply this framework to a small database of brain images for detecting structure abnormality.

Anomaly Detection Template Matching