no code implementations • 31 May 2019 • Raif M. Rustamov, James T. Klosowski
This paper introduces an approach for detecting differences in the first-order structures of spatial point patterns.
no code implementations • 10 Jan 2019 • Raif M. Rustamov
The Maximum Mean Discrepancy (MMD) has found numerous applications in statistics and machine learning, most recently as a penalty in the Wasserstein Auto-Encoder (WAE).
no code implementations • CVPR 2013 • Nan Hu, Raif M. Rustamov, Leonidas Guibas
In this paper, we consider the weighted graph matching problem with partially disclosed correspondences between a number of anchor nodes.
no code implementations • 14 Sep 2017 • Raif M. Rustamov, James T. Klosowski
In this paper, we consider the interpretability of the foundational Laplacian-based semi-supervised learning approaches on graphs.
no code implementations • CVPR 2014 • Nan Hu, Raif M. Rustamov, Leonidas Guibas
We also introduce the pairwise heat kernel distance as a stable second order compatibility term; we justify its plausibility by showing that in a certain limiting case it converges to the classical adjacency matrix-based second order compatibility function.