16 citations · 29 across the 10 of their papers we have counts for
4 papers · 1 filter
A Universal Nearest-Neighbor Estimator for Intrinsic Dimensionality
Eng-Jon Ong, Omer Bobrowski, Gesine Reinert +1
Estimating the intrinsic dimensionality (ID) of data is a fundamental problem in machine learning and computer vision, providing insight into the true degrees of freedom underlying…
Approximating Metric Magnitude of Point Sets
Rayna Andreeva, James Ward, Primoz Skraba +2
Metric magnitude is a measure of the "size" of point clouds with many desirable geometric properties. It has been adapted to various mathematical contexts and recent work suggests…
A Topology Layer for Machine Learning
Rickard Brüel-Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath +3
Topology applied to real world data using persistent homology has started to find applications within machine learning, including deep learning. We present a differentiable topolog…
A Comparison of Relaxations of Multiset Cannonical Correlation Analysis and Applications
Jan Rupnik, Primoz Skraba, John Shawe-Taylor +1
Canonical correlation analysis is a statistical technique that is used to find relations between two sets of variables. An important extension in pattern analysis is to consider mo…