So sánh phương pháp

	Học chuyển giao với Bộ Tự mã hóa Biến phân	Generative Adversarial Network
Lĩnh vực	Học sâu	Học sâu
Họ	Machine learning	Machine learning
Năm ra đời	2014 (VAE); 2010 (transfer learning survey)	2014
Người khởi xướng	Kingma, D. P. & Welling, M. (VAE); transfer learning framework from Pan & Yang	Goodfellow, I. et al.
Loại	Generative model with transferred encoder/decoder	Generative deep learning (adversarial two-network game)
Công trình gốc	Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes. International Conference on Learning Representations (ICLR 2014).	Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS.
Tên gọi khác	TL-VAE, pretrained VAE, VAE transfer learning, fine-tuned variational autoencoder	Üretici Çekişmeli Ağ (GAN), GAN, generative adversarial nets, adversarial network
Liên quan	6	4
Tóm tắt	Transfer Learning with a Variational Autoencoder (TL-VAE) reuses an encoder and/or decoder pre-trained on a large source dataset and adapts it to a smaller target domain. By inheriting a rich probabilistic latent space rather than starting from random weights, TL-VAE dramatically reduces the amount of target-domain data needed for high-quality generation or representation learning.	A Generative Adversarial Network (GAN), introduced by Ian Goodfellow and colleagues in 2014, produces realistic synthetic data through the competition of two neural networks — a generator and a discriminator. It is widely used for image synthesis, data augmentation, and distribution estimation.