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Machine learningDeep learning / NLP / CV

Variational Autoencoder ya Kujisimamia Yenyewe

Variational Autoencoder ya Kujisimamia Yenyewe (SS-VAE) inachanganya ujifunzaji wa nafasi fiche ya uzalishaji wa VAE ya kawaida na kazi za awali za kujisimamia — kama vile uongezaji wa kulinganisha, ujenzi uliofichwa, au utabiri wa mzunguko — ili kujifunza uwakilishi tajiri zaidi na uliotenganishwa kutoka kwa data isiyo na lebo bila dalili zozote za kuingilia kati.

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Vyanzo

  1. Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes. In Proceedings of the 2nd International Conference on Learning Representations (ICLR 2014). link
  2. Liu, X., Zhang, F., Hou, Z., Mian, L., Wang, Z., Zhang, J., & Tang, J. (2021). Self-Supervised Learning: Generative or Contrastive. IEEE Transactions on Knowledge and Data Engineering, 35(1), 857–876. DOI: 10.1109/TKDE.2021.3090866

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Self-supervised Variational Autoencoder (SS-VAE). ScholarGate. https://scholargate.app/sw/deep-learning/self-supervised-variational-autoencoder

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Imerejelewa na

ScholarGateSelf-supervised Variational Autoencoder (Self-supervised Variational Autoencoder (SS-VAE)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/self-supervised-variational-autoencoder · Seti ya data: https://doi.org/10.5281/zenodo.20539026