1.3k citations · 3.7k across the 55 of their papers we have counts for
11 papers · 1 filter
Clustering in graphs and hypergraphs with categorical edge labels
Ilya Amburg, Nate Veldt, Austin R. Benson
Modern graph or network datasets often contain rich structure that goes beyond simple pairwise connections between nodes. This calls for complex representations that can capture, f…
Retrieving Top Weighted Triangles in Graphs
Raunak Kumar, Paul Liu, Moses Charikar +1
Pattern counting in graphs is a fundamental primitive for many network analysis tasks, and a number of methods have been developed for scaling subgraph counting to large graphs. Ma…
Incrementally Updated Spectral Embeddings
Vasileios Charisopoulos, Austin R. Benson, Anil Damle
Several fundamental tasks in data science rely on computing an extremal eigenspace of size , where is the underlying problem dimension. For example, spectral clusterin…
Pairwise Link Prediction
Huda Nassar, Austin R. Benson, David F. Gleich
Link prediction is a common problem in network science that transects many disciplines. The goal is to forecast the appearance of new links or to find links missing in the network.…
Network Density of States
Kun Dong, Austin R. Benson, David Bindel
Spectral analysis connects graph structure to the eigenvalues and eigenvectors of associated matrices. Much of spectral graph theory descends directly from spectral geometry, the s…
Graph-based Semi-Supervised & Active Learning for Edge Flows
Junteng Jia, Michael T. Schaub, Santiago Segarra +1
We present a graph-based semi-supervised learning (SSL) method for learning edge flows defined on a graph. Specifically, given flow measurements on a subset of edges, we want to pr…
Planted Hitting Set Recovery in Hypergraphs
Ilya Amburg, Jon Kleinberg, Austin R. Benson
In various application areas, networked data is collected by measuring interactions involving some specific set of core nodes. This results in a network dataset containing the core…
Measuring Directed Triadic Closure with Closure Coefficients
Hao Yin, Austin R. Benson, Johan Ugander
Recent work studying triadic closure in undirected graphs has drawn attention to the distinction between measures that focus on the "center" node of a wedge (i.e., length-2 path) v…
Neural Jump Stochastic Differential Equations
Junteng Jia, Austin R. Benson
Many time series are effectively generated by a combination of deterministic continuous flows along with discrete jumps sparked by stochastic events. However, we usually do not hav…
Network interpolation
Thomas Reeves, Anil Damle, Austin R. Benson
Given a set of snapshots from a temporal network we develop, analyze, and experimentally validate a so-called network interpolation scheme. Our method allows us to build a plausibl…
Modeling and Analysis of Tagging Networks in Stack Exchange Communities
Xiang Fu, Shangdi Yu, Austin R. Benson
Large Question-and-Answer (Q&A) platforms support diverse knowledge curation on the Web. While researchers have studied user behavior on the platforms in a variety of contexts, the…