Unverified50% confidenceFactExact time
Andrew Ng 和 Michael Jordan 在 2001 年的论文中比较生成模型与判别模型，结论是生成模型在小样本时更具优势，判别模型在大数据量时通常表现更好
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8/29/2026
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Unverified生成模型在小样本时更具优势，判别模型在大数据量时通常表现更好76% similarUnverified生成式模型建模联合概率 P(x,y) 或数据分布 P(x)，判别式模型直接建模条件概率 P(y|x)，该区分最初由 Andrew Ng 和 Michael Jordan 在 2001 年的论文中系统比较70% similarUnverifiedThe model used is Zhipu (rated by the author as performing relatively well domestically), with concurrency control implemented to address its rate-limiting issues.68% similarUnverifiedScore Matching和Langevin Dynamics为扩散模型提供了等价的理论视角，模型本质上学习数据分布的得分函数，这一视角由宋飏（Yang Song）等人阐明66% similarUnverifiedWhen selecting models, one should not only look at accuracy on standard datasets but also pay attention to out-of-domain generalization robustness on unfamiliar data.65% similar
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