2018/05/24 by Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Ramamurthy, Karthikeyan Natesan +3 · 1 citation
Computer Science · Mathematics · Neuroscience · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neuroinflammation and Neurodegeneration Mechanisms #Rough Sets and Fuzzy Logic #Topological and Geometric Data Analysis #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.1805.09949
Reproducible software available, 17 pages, 10 figures, 12 tables
arxiv created 2018/05/25 · openalex publication_date 2018/05/25 · arxiv updated 2018/05/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose the labeled Čech complex, the plain labeled Vietoris-Rips complex, and the locally scaled labeled Vietoris-Rips complex to perform persistent homology inference of decision boundaries in classification tasks. We provide theoretical conditions and analysis for recovering the homology of a decision boundary from samples. Our main objective is quantification of deep neural network complexity to enable matching of datasets to pre-trained models; we report results for experiments using MNIST, FashionMNIST, and CIFAR10.