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Found 5 papers, 0 papers with code
LUMAWIG: Un-bottling the bottleneck distance for zero dimensional persistence diagrams at scale
We present LUMÁWIG, a novel efficient algorithm to compute dimension zero bottleneck distance between two persistence diagrams of a specific kind which outperforms all other publicly available algorithm in runtime and accuracy.
The Problem with Metrics is a Fundamental Problem for AI
Optimizing a given metric is a central aspect of most current AI approaches, yet overemphasizing metrics leads to manipulation, gaming, a myopic focus on short-term goals, and other unexpected negative consequences.
Classification of Single-lead Electrocardiograms: TDA Informed Machine Learning
Atrial Fibrillation is a heart condition characterized by erratic heart rhythms caused by chaotic propagation of electrical impulses in the atria, leading to numerous health complications.
Multiclass Total Variation Clustering
Ideas from the image processing literature have recently motivated a new set of clustering algorithms that rely on the concept of total variation.
Convergence and Energy Landscape for Cheeger Cut Clustering
Unsupervised clustering of scattered, noisy and high-dimensional data points is an important and difficult problem.
