Magnetic field prediction using generative adversarial networks

This publication has 23 references indexed in Scilit:

• Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules
  ACS Central Science, 2018
• Globally and locally consistent image completion
  ACM Transactions on Graphics, 2017
• Measurement and tricubic interpolation of the magnetic field for the OLYMPUS experiment
  Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2016
• Deep Residual Learning for Image Recognition
  2016
• 3-Axis magnetic field mapping and fusion for indoor localization
  2012
• OBTAINING POTENTIAL FIELD SOLUTIONS WITH SPHERICAL HARMONICS AND FINITE DIFFERENCES
  The Astrophysical Journal, 2011
• A New Method for Polar Field Interpolation
  Solar Physics, 2011
• Interpolation of externally-caused magnetic fields over large sparse arrays using Spherical Elementary Current Systems
  Annales Geophysicae, 2010
• EMAG2: A 2–arc min resolution Earth Magnetic Anomaly Grid compiled from satellite, airborne, and marine magnetic measurements
  Geochemistry, Geophysics, Geosystems, 2009
• Multilayer feedforward networks are universal approximators
  Neural Networks, 1989