activity
20182021
most citedGraph Signal Processing for Infrastructure Resilience: Suitability and Future Directions

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP2021

Detecting Anomalous Swarming Agents with Graph Signal Processing

Kevin Schultz, Anshu Saksena, Elizabeth P. Reilly +2

Collective motion among biological organisms such as insects, fish, and birds has motivated considerable interest not only in biology but also in distributed robotic systems. In a…

cs.CV2021

Towards Indirect Top-Down Road Transport Emissions Estimation

Ryan Mukherjee, Derek Rollend, Gordon Christie +4

Road transportation is one of the largest sectors of greenhouse gas (GHG) emissions affecting climate change. Tackling climate change as a global community will require new capabil…

cond-mat.soft2021

Analyzing Collective Motion Using Graph Fourier Analysis

Kevin Schultz, Marisel Villafane-Delgado, Elizabeth P. Reilly +2

Collective motion in animal groups, such as swarms of insects, flocks of birds, and schools of fish, are some of the most visually striking examples of emergent behavior. Empirical…

eess.SP20201 cited

Graph Signal Processing for Infrastructure Resilience: Suitability and Future Directions

Kevin Schultz, Marisel Villafane-Delgado, Elizabeth P. Reilly +2

Graph signal processing (GSP) is an emerging field developed for analyzing signals defined on irregular spatial structures modeled as graphs. Given the considerable literature rega…

cs.AI2018

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Ritchie Lee, Ole J. Mengshoel, Anshu Saksena +5

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collisi…