AI Simplifies Image Generation With Score-of-Mixture Training
New AI method, Score-of-Mixture Training (SMT), simplifies image generation with competitive performance on CIFAR-10 & ImageNet datasets. Simple implementation with minimal tuning required.
This is a Plain English Papers summary of a research paper called New AI Method Makes Image Generation Simpler and More Efficient with Score-of-Mixture Training. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter. Overview New framework called Score-of-Mixture Training (SMT) for one-step generative models Uses alpha-skew Jensen-Shannon divergence to estimate score mixtures Supports both training from scratch and distillation from existing models Competitive performance on CIFAR-10 and ImageNet datasets Simple implementation with minimal tuning r...