Optimal and Diffusion Transports in Machine Learning 事件

Optimal and Diffusion Transports in Machine Learning arXiv:2512.06797v2 Announce Type: replace-cross Abstract: Several problems in machine learning are naturally expressed as the design and analysis of time-evolving probability distributions. This includes sampling via diffusion methods, optimizing the weights of neural networks, and analyzing the evolution of token distributions across layers of large language models. While the targeted applications differ (samples, weights, tokens), their mat