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- Fermi National Accelerator LaboratoryUS27 papers
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5 papers · 1 filter
Data Dropout: Optimizing Training Data for Convolutional Neural Networks
Tianyang Wang, Jun Huan, Bo Li
Deep learning models learn to fit training data while they are highly expected to generalize well to testing data. Most works aim at finding such models by creatively designing arc…
Instance-based Deep Transfer Learning
Tianyang Wang, Jun Huan, Michelle Zhu
Deep transfer learning recently has acquired significant research interest. It makes use of pre-trained models that are learned from a source domain, and utilizes these models for…
Artificial Neural Networks in Fluid Dynamics: A Novel Approach to the Navier-Stokes Equations
Megan McCracken
Neural networks have been used to solve different types of large data related problems in many different fields.This project takes a novel approach to solving the Navier-Stokes Equ…
New Perspectives on Neighborhood-Prime Labelings of Graphs
John Asplund, N. Bradley Fox, Arran Hamm
Neighborhood-prime labeling is a variation of prime labeling. A labeling is a neighborhood-prime labeling if for each vertex with degree greater t…
The Dark Energy Survey Data Release 1
T. M. C. Abbott, F. B. Abdalla, S. Allam +199
We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single epoch images, coadded images, coadded source catalogs, and associated pro…