26 citations · 40 across the 5 of their papers we have counts for
5 papers
Learning Graph-Level Representations with Recurrent Neural Networks
Yu Jin, Joseph F. JaJa
Recently a variety of methods have been developed to encode graphs into low-dimensional vectors that can be easily exploited by machine learning algorithms. The majority of these m…
A High Performance Implementation of Spectral Clustering on CPU-GPU Platforms
Yu Jin, Joseph F. JaJa
Spectral clustering is one of the most popular graph clustering algorithms, which achieves the best performance for many scientific and engineering applications. However, existing…
A Data-Driven Approach to Extract Connectivity Structures from Diffusion Tensor Imaging Data
Yu Jin, Joseph F. JaJa, Rong Chen +1
Diffusion Tensor Imaging (DTI) is an effective tool for the analysis of structural brain connectivity in normal development and in a broad range of brain disorders. However efforts…
Graph Coarsening with Preserved Spectral Properties
Yu Jin, Andreas Loukas, Joseph F. JaJa
Large-scale graphs are widely used to represent object relationships in many real world applications. The occurrence of large-scale graphs presents significant computational challe…
Scalable Algorithms for Generating and Analyzing Structural Brain Networks with a Varying Number of Nodes
Yu Jin, Joseph F. JaJa, Rong Chen +1
Diffusion Magnetic Resonance Imaging (MRI) exploits the anisotropic diffusion of water molecules in the brain to enable the estimation of the brain's anatomical fiber tracts at a r…