activity
20152019
most citedImage Classification with Hierarchical Multigraph Networks

26 citations · 40 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CR2019

Deep Complex Networks for Protocol-Agnostic Radio Frequency Device Fingerprinting in the Wild

Ioannis Agadakos, Nikolaos Agadakos, Jason Polakis +1

Researchers have demonstrated various techniques for fingerprinting and identifying devices. Previous approaches have identified devices from their network traffic or transmitted s…

cs.CV201926 cited

Image Classification with Hierarchical Multigraph Networks

Boris Knyazev, Xiao Lin, Mohamed R. Amer +1

Graph Convolutional Networks (GCNs) are a class of general models that can learn from graph structured data. Despite being general, GCNs are admittedly inferior to convolutional ne…

cs.LG20197 cited

Data-Efficient Mutual Information Neural Estimator

Xiao Lin, Indranil Sur, Samuel A. Nastase +3

Measuring Mutual Information (MI) between high-dimensional, continuous, random variables from observed samples has wide theoretical and practical applications. Recent work, MINE (B…

cs.LG2019

Understanding Attention and Generalization in Graph Neural Networks

Boris Knyazev, Graham W. Taylor, Mohamed R. Amer

We aim to better understand attention over nodes in graph neural networks (GNNs) and identify factors influencing its effectiveness. We particularly focus on the ability of attenti…

cs.LG2018

Spectral Multigraph Networks for Discovering and Fusing Relationships in Molecules

Boris Knyazev, Xiao Lin, Mohamed R. Amer +1

Spectral Graph Convolutional Networks (GCNs) are a generalization of convolutional networks to learning on graph-structured data. Applications of spectral GCNs have been successful…

cs.CV2018

Human Motion Modeling using DVGANs

Xiao Lin, Mohamed R. Amer

We present a novel generative model for human motion modeling using Generative Adversarial Networks (GANs). We formulate the GAN discriminator using dense validation at each time-s…