Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models 事件

Markov Chain Decoders Overcome the Heavy-Tail Limitations of Lipschitz Generative Models arXiv:2605.18931v2 Announce Type: replace-cross Abstract: Heavy-tailed distributions are prevalent in performance evaluation, network traffic, and risk modeling. This behavior poses a fundamental challenge for modern deep generative models. Standard Variational Autoencoders (VAEs) employ Gaussian decoder likelihoods and Lipschitz-constrained neural networks, a combination that is structurally incapable of p