পদ্ধতির তুলনা করুন

	Semi-supervised Diffusion Model	জেনারেটিভ অ্যাডভারসারিয়াল নেটওয়ার্ক
ক্ষেত্র	গভীর শিখন	গভীর শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	2020–2022	2014
প্রবর্তক	Multiple groups (Ho et al., Song et al., and successors)	Goodfellow, I. et al.
ধরন	Generative model with semi-supervised guidance	Generative deep learning (adversarial two-network game)
মৌলিক উৎস	Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., & Ganguli, S. (2015). Deep Unsupervised Learning using Nonequilibrium Thermodynamics. Proceedings of the 32nd International Conference on Machine Learning (ICML), 2256–2265.	Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS.
অপর নাম	Semi-supervised DDPM, Label-guided diffusion model, Semi-supervised score-based generative model, SSL diffusion	Üretici Çekişmeli Ağ (GAN), GAN, generative adversarial nets, adversarial network
সম্পর্কিত	3	4
সারসংক্ষেপ	A semi-supervised diffusion model extends the denoising diffusion probabilistic framework to settings where only a fraction of training samples carry class labels. By combining an unconditional diffusion backbone with a lightweight classifier trained on labeled examples, it learns to generate high-quality, label-conditioned outputs while still exploiting the structure in unlabeled data.	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.