Unsupervised real-world knowledge extraction via disentangled variational autoencoders for photon diagnostics

HIGHLIGHTS

  • who: Gregor Hartmann from the University of have published the Article: Unsupervised real-world knowledge extraction via disentangled variational autoencoders for photon diagnostics, in the Journal: Scientific Reports Scientific Reports
  • what: A magnetic bottle u00adexperiment21 was performed in parallel with the study and its data is used as a cross reference for the wavelength, which is presented in the SI.
  • future: During training the network continues training with the same one million samples for a fixed number of epochs until the data is replaced by another one million samples from another file and . . .

     

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