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原文
OpenAI News·· 2019-03-21AI 评分23

OpenAI 提出能量模型隐式生成与泛化方法

Implicit generation and generalization methods for energy-based models

AI 导读

OpenAI 在能量模型(EBMs)的稳定可扩展训练方面取得进展,其样本质量与泛化能力优于现有模型。该方法通过持续计算优化答案,低温下生成效果可与 GAN 竞争,同时具备似然模型的模式覆盖保证。

原文

We’ve made progress towards stable and scalable training of energy-based models (EBMs) resulting in better sample quality and generalization ability than existing models. Generation in EBMs spends more compute to continually refine its answers and doing so can generate samples competitive with GANs at low temperatures, while also having mode coverage guarantees of likelihood-based models. We hope these findings stimulate further research into this promising class of models.

来源:OpenAI News · openai.com