124 citations
- San Diego State UniversityUS6 papers
- University of California San DiegoUS6 papers
- Lawrence Berkeley National LaboratoryUS3 papers
- Naval Information Warfare Systems CommandUS3 papers
- Daegu Gyeongbuk Institute of Science and TechnologyKR2 papers
- Hypres (United States)US2 papers
- National Institute of Standards and TechnologyUS2 papers
- University of California, IrvineUS2 papers
- University of Illinois Urbana-ChampaignUS2 papers
- Ben-Gurion University of the NegevIL1 paper
- Calspan-University of Buffalo Research CenterUS1 paper
- Center for Nanoscale Science and TechnologyUS1 paper
26 papers
Forecasting Local Ionospheric Parameters Using Transformers
Daniel J. Alford-Lago, Christopher W. Curtis, Alexander T. Ihler +2
We present a novel method for forecasting key ionospheric parameters using transformer-based neural networks. The model provides accurate forecasts and uncertainty quantification o…
Investigation of moving objects through atmospheric turbulence from a non-stationary platform
Nicholas Ferrante, Jerome Gilles, Shibin Parameswaran
In this work, we extract the optical flow field corresponding to moving objects from an image sequence of a scene impacted by atmospheric turbulence \emph{and} captured from a movi…
Skyrmion-Excited Spin Wave Fractal Network
Nan Tang, W. L. N. C. Liyanage, Sergio A. Montoya +9
Magnetic skyrmions exhibit unique, technologically relevant pseudo-particle behaviors which arise from their topological protection, including well-defined, three-dimensional dynam…
Novelty Accommodating Multi-Agent Planning in High Fidelity Simulated Open World
James Chao, Wiktor Piotrowski, Roni Stern +4
Autonomous agents operating within real-world environments often rely on automated planners to ascertain optimal actions towards desired goals or the optimization of a specified ob…
Towards an effective mass model for the quasi-1D magnesium diboride superconducting nanostructures
Wojciech Julian Pasek, Marcos H. Degani, Marcio C. de Andrade +1
We developed a parabolic effective mass model with the aim to describe the in-plane constricted superconductivity in few-monolayer MgB. The model was employed to study a constr…
Deep Learning Enhanced Dynamic Mode Decomposition
Daniel J. Alford-Lago, Christopher W. Curtis, Alexander T. Ihler +1
Koopman operator theory shows how nonlinear dynamical systems can be represented as an infinite-dimensional, linear operator acting on a Hilbert space of observables of the system.…