998 citations
- DEVCOM Army Research LaboratoryUS45 papers
- U.S. Army Engineer Research and Development CenterUS21 papers
- United States Army Combat Capabilities Development CommandUS20 papers
- United States Department of the ArmyUS18 papers
- United States Army Research OfficeUS17 papers
- U.S. Army Combat Capabilities Development Command Aviation & Missile Center15 papers
- Duke UniversityUS14 papers
- U.S. Army Aviation and Missile CommandUS11 papers
- Pennsylvania State UniversityUS9 papers
- Massachusetts Institute of TechnologyUS8 papers
- Oakland UniversityUS7 papers
- University of North TexasUS7 papers
7 papers · 1 filter
Programmable Multi-Node Quantum Network Design and Simulation
Venkat R. Dasari, Ronald J. Sadlier, Ryan Prout +2
Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to…
Weakly Supervised Localization using Deep Feature Maps
Archith J. Bency, Heesung Kwon, Hyungtae Lee +2
Object localization is an important computer vision problem with a variety of applications. The lack of large scale object-level annotations and the relative abundance of image-lev…
An introduction to sampling via measure transport
Youssef Marzouk, Tarek Moselhy, Matthew Parno +1
We present the fundamentals of a measure transport approach to sampling. The idea is to construct a deterministic coupling---i.e., a transport map---between a complex "target" prob…
Information Diffusion of Topic Propagation in Social Media
Shahin Mahdizadehaghdam, Han Wang, Hamid Krim +1
Real-world social and/or operational networks consist of agents with associated states, whose connectivity forms complex topologies. This complexity is further compounded by interc…
Quantum-Noise-Limited Sensitivity-Enhancement of a Passive Optical Cavity by a Fast-Light Medium
David D. Smith, H. A. Luckay, Hongrok Chang +1
We demonstrate for a passive optical cavity containing a dispersive atomic medium, the increase in scale factor near the critical anomalous dispersion is not cancelled by mode broa…
Practical Black-Box Attacks against Machine Learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow +3
Machine learning (ML) models, e.g., deep neural networks (DNNs), are vulnerable to adversarial examples: malicious inputs modified to yield erroneous model outputs, while appearing…