research
∙
08/23/2023
Quantifying degeneracy in singular models via the learning coefficient
Deep neural networks (DNN) are singular statistical models which exhibit...
share
research
∙
05/20/2023
Technical outlier detection via convolutional variational autoencoder for the ADMANI breast mammogram dataset
The ADMANI datasets (annotated digital mammograms and associated non-ima...
research
∙
02/13/2023
Variational Bayesian Neural Networks via Resolution of Singularities
In this work, we advocate for the importance of singular learning theory...
research
∙
05/27/2022
Counterfactual Fairness with Partially Known Causal Graph
Fair machine learning aims to avoid treating individuals or sub-populati...
research
∙
10/22/2020
Deep Learning is Singular, and That's Good
In singular models, the optimal set of parameters forms an analytic set ...
research
∙
08/25/2020
The Fairness-Accuracy Pareto Front
Mitigating bias in machine learning is a challenging task, due in large ...
research
∙
08/21/2020
Automating the assessment of biofouling in images using expert agreement as a gold standard
Biofouling is the accumulation of organisms on surfaces immersed in wate...
research
∙
06/18/2020