8 citations · 15 across the 6 of their papers we have counts for
6 papers
Efficient Document Image Classification Using Region-Based Graph Neural Network
Jaya Krishna Mandivarapu, Eric Bunch, Qian You +1
Document image classification remains a popular research area because it can be commercialized in many enterprise applications across different industries. Recent advancements in l…
Weighting vectors for machine learning: numerical harmonic analysis applied to boundary detection
Eric Bunch, Jeffery Kline, Daniel Dickinson +2
Metric space magnitude, an active field of research in algebraic topology, is a scalar quantity that summarizes the effective number of distinct points that live in a general metri…
Geometric feature performance under downsampling for EEG classification tasks
Bryan Bischof, Eric Bunch
We experimentally investigate a collection of feature engineering pipelines for use with a CNN for classifying eyes-open or eyes-closed from electroencephalogram (EEG) time-series…
Simplicial 2-Complex Convolutional Neural Nets
Eric Bunch, Qian You, Glenn Fung +1
Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph. While useful, graph structure…
Practical applications of metric space magnitude and weighting vectors
Eric Bunch, Daniel Dickinson, Jeffery Kline +1
Metric space magnitude, an active subject of research in algebraic topology, originally arose in the context of biology, where it was used to represent the effective number of dist…
Approximating the Convex Hull via Metric Space Magnitude
Glenn Fung, Eric Bunch, Dan Dickinson
Magnitude of a finite metric space and the related notion of magnitude functions on metric spaces is an active area of research in algebraic topology. Magnitude originally arose in…