Reconstructing 3D objects from 2D images is both challenging for our brains and machine
learning algorithms. To support this spatial reasoning task, contextual information about the …

In semiconductor manufacturing, wafer map defect pattern provides critical information for
facility maintenance and yield management, so the classification of defect patterns is one of …

The nycthemeral transcriptome embodies all genes displaying a rhythmic variation of their
mRNAs periodically every 24 hours, including but not restricted to circadian genes. In this …

A method for the use of persistent homology in the statistical analysis of landmark-based
shape data is given. Three-dimensional landmark configurations are used as input for …

Topological features based on persistent homology capture high-order structural information
so as to augment graph neural network methods. However, computing extended persistent …

Topological data analysis refers to a broad set of techniques that are used to make
inferences about the shape of data. A popular topological summary is the persistence …

This paper proposes a novel topological learning framework that integrates networks of
different sizes and topology through persistent homology. Such challenging task is made …

The pathogenic yeast Cryptococcus neoformans causes fungal meningitis in immune-
compromised patients. Cell proliferation in the budding yeast form is required for C …

We introduce and study the barcode entropy for geodesic flows of closed Riemannian
manifolds, which measures the exponential growth rate of the number of not-too-short bars …

A time series can often be characterized using machine learning techniques, which require
feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized …