为了证明可行性，他们测试了 GAN 里流行的 StyleGAN2，通过新的理论进行最简升级（修改后改名为「R3GAN」）。结果虽然模型变得更简单了，但 R3GAN 在图像生成和数据增强任务上性能还是超过了所有 GAN 模型和扩散模型。

【新智元导读】 GAN已死？不，它卷土重来了！布朗大学和康奈尔大学的研究者刚刚提出了R3GAN，充分利用现代架构设计，彻底摒弃临时技巧，一半参数就能碾压扩散模型。网友惊呼：游戏规则要改变了！

This project focuses on classifying handwritten digits from the MNIST dataset. It explores and compares the performance of various machine learning models including Neural Networks, SVM, and KNN. The ...

It trains GAN models using the Fashion MNIST dataset. It applies Gaussian AHP to optimize hyperparameters based on multiple performance criteria, such as the quality of generated images, training ...

STMicroelectronics backs Innoscience’s IPO, boosting GaN semiconductor market potential. Despite Innoscience and its partners not releasing any official statements, according to this document, ...