Neural sequence-to-sequence models for low-resource morphology

Katharina Kann

doi:10.5282/edoc.24353

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Neural sequence-to-sequence models for low-resource morphology

Katharina Kann

Year: 2019 Journal: Elektronische Hochschulschriften der LMU München (Ludwig-Maximilians-Universität München) Publisher: Ludwig-Maximilians-Universität München

DOI: 10.5282/edoc.24353

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Keywords:

Sequence (biology) Computer science Artificial intelligence Biology Genetics

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Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Digital Imaging for Blood Diseases

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Neural sequence-to-sequence models for low-resource morphology

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