74 citations · 162 across the 36 of their papers we have counts for
5 papers · 1 filter
Hodge-Laplacian of Brain Networks
D. Vijay Anand, Moo K. Chung
The closed loops or cycles in a brain network embeds higher order signal transmission paths, which provide fundamental insights into the functioning of the brain. In this work, we…
Lattice Paths for Persistent Diagrams
Moo K. Chung, Hernando Ombao
Persistent homology has undergone significant development in recent years. However, one outstanding challenge is to build a coherent statistical inference procedure on persistent d…
Graph Theory in Brain Networks
Moo K. Chung
Recent developments in graph theoretic analysis of complex networks have led to deeper understanding of brain networks. Many complex networks show similar macroscopic behaviors des…
Reviews: Topological Distances and Losses for Brain Networks
Moo K. Chung, Alexander Smith, Gary Shiu
Almost all statistical and machine learning methods in analyzing brain networks rely on distances and loss functions, which are mostly Euclidean or matrix norms. The Euclidean or m…
Cosine Series Representation
Moo K. Chung
We present a functional data analysis (FDA) framework based on explicit orthonormal basis expansion for modeling and denoising complex biomedical signals. Observed functional data…