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Proses Gaussian Terpandu Mandiri

Self-supervised Gaussian Process (SSL-GP) menggabungkan kuantifikasi ketidakpastian yang berprinsip dari Gaussian process dengan pra-pelatihan swa-awasi (self-supervised pretraining), mempelajari kernel ekspresif atau representasi laten dari data tak berlabel sebelum menyesuaikan GP pada kumpulan data berlabel kecil. Hal ini membuat pendekatan tersebut sangat ampuh dalam rezim data berlabel rendah di mana GP konvensional akan mengalami *overfitting* atau menghasilkan estimasi ketidakpastian yang kurang terkalibrasi.

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Sumber

  1. Fortuin, V., Rätsch, G., & Mandt, S. (2020). GP-VAE: Deep probabilistic time series imputation using Gaussian process variational autoencoders. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 108, 1651–1661. link
  2. Gaussian process. Wikipedia. link

Cara menyitasi halaman ini

ScholarGate. (2026, June 3). Self-supervised Gaussian Process (SSL-GP). ScholarGate. https://scholargate.app/id/machine-learning/self-supervised-gaussian-process

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ScholarGateSelf-supervised Gaussian Process (Self-supervised Gaussian Process (SSL-GP)). Diakses 2026-06-15 dari https://scholargate.app/id/machine-learning/self-supervised-gaussian-process · Set data: https://doi.org/10.5281/zenodo.20539026