Zeyu Michael Li

Jointly training path and flow networks with a novel alignment objective unlocks improved generative model performance by preventing path overfitting and low-entropy bottlenecks.

Anisotropic noise schedules, optimized via a novel variational framework, can significantly boost diffusion model performance across various datasets and NFE regimes.