Search Results for author: Raif M. Rustamov

Found 5 papers, 0 papers with code

Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns

no code implementations31 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.

Point Processes Two-sample testing

Closed-form Expressions for Maximum Mean Discrepancy with Applications to Wasserstein Auto-Encoders

no code implementations10 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).

Graph Matching with Anchor Nodes: A Learning Approach

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.

Graph Matching

Interpretable Graph-Based Semi-Supervised Learning via Flows

no code implementations14 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.

Stable and Informative Spectral Signatures for Graph Matching

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.

Graph Matching Informativeness

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