3 papers
stat.ML2019
Bayesian Topological Learning for Brain State Classification
Farzana Nasrin, Christopher Oballe, David L. Boothe +1
Investigation of human brain states through electroencephalograph (EEG) signals is a crucial step in human-machine communications. However, classifying and analyzing EEG signals ar…
stat.ME2019
A Bayesian Framework for Persistent Homology
Vasileios Maroulas, Farzana Nasrin, Christopher Oballe
Persistence diagrams offer a way to summarize topological and geometric properties latent in datasets. While several methods have been developed that utilize persistence diagrams i…
math.ST2018
Nonparametric Estimation of Probability Density Functions of Random Persistence Diagrams
Joshua Lee Mike, Vasileios Maroulas
We introduce a nonparametric way to estimate the global probability density function for a random persistence diagram. Precisely, a kernel density function centered at a given pers…