150 citations · 165 across the 9 of their papers we have counts for
10 papers
First fast radio burst search campaign at the Argentine Institute of Radio Astronomy
Carlos O. Lousto, Harsh Prajapati, Ezequiel Zubieta +7
Fast radio bursts (FRBs) are intense millisecond-duration radio transients of extragalactic origin whose physical nature remains under active investigation, and which also serve as…
Vela Pulsar: Single Pulses Analysis with Machine Learning Techniques
Carlos O. Lousto, Ryan Missel, Harsh Prajapati +12
We study individual pulses of Vela (PSR\ B0833-45\,/\,J0835-4510) from daily observations of over three hours (around 120,000 pulses per observation), performed simultaneously with…
Near Real-time Learning and Extraction of Attack Models from Intrusion Alerts
Shanchieh Jay Yang, Ahmet Okutan, Gordon Werner +3
Critical and sophisticated cyberattacks often take multitudes of reconnaissance, exploitations, and obfuscation techniques to penetrate through well protected enterprise networks.…
Memory Efficient Experience Replay for Streaming Learning
Tyler L. Hayes, Nathan D. Cahill, Christopher Kanan
In supervised machine learning, an agent is typically trained once and then deployed. While this works well for static settings, robots often operate in changing environments and m…
Compassionately Conservative Balanced Cuts for Image Segmentation
Nathan D. Cahill, Tyler L. Hayes, Renee T. Meinhold +1
The Normalized Cut (NCut) objective function, widely used in data clustering and image segmentation, quantifies the cost of graph partitioning in a way that biases clusters or segm…
Robust Spatial Filtering with Graph Convolutional Neural Networks
Felipe Petroski Such, Shagan Sah, Miguel Dominguez +5
Convolutional Neural Networks (CNNs) have recently led to incredible breakthroughs on a variety of pattern recognition problems. Banks of finite impulse response filters are learne…
Relationships Between Characteristic Path Length, Efficiency, Clustering Coefficients, and Graph Density
Alexander Strang, Oliver Haynes, Nathan D. Cahill +1
The graph theoretic properties of the clustering coefficient, characteristic (or average) path length, global and local efficiency, provide valuable information regarding the struc…
Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation
Renee T. Meinhold, Tyler L. Hayes, Nathan D. Cahill
Image segmentation is a popular area of research in computer vision that has many applications in automated image processing. A recent technique called piecewise flat embeddings (P…
Multiple-View Spectral Clustering for Group-wise Functional Community Detection
Nathan D. Cahill, Harmeet Singh, Chao Zhang +6
Functional connectivity analysis yields powerful insights into our understanding of the human brain. Group-wise functional community detection aims to partition the brain into clus…
Integrating Atlas and Graph Cut Methods for LV Segmentation from Cardiac Cine MRI
Shusil Dangi, Nathan Cahill, Cristian A. Linte
Magnetic Resonance Imaging (MRI) has evolved as a clinical standard-of-care imaging modality for cardiac morphology, function assessment, and guidance of cardiac interventions. All…