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FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data.

Lisa WeijlerFlorian KowarschMichael ReiterPedro HermosillaMargarita Maurer-GranofszkyMichael N. Dworzak
Published in: WACV (2024)
Keyphrases
  • learning process
  • supervised learning
  • training data
  • support vector
  • feature set
  • online learning
  • learning problems
  • machine learning
  • prior knowledge
  • knowledge acquisition
  • learning systems
  • learning spaces