Nonlinear denoising score matching for enhanced learning of structured distributions

Documenti analoghi

• Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows
  di: Gu, Hyemin, et al.
  Pubblicazione: (2024)
• Sample Complexity of Probability Divergences under Group Symmetry
  di: Chen, Ziyu, et al.
  Pubblicazione: (2023)
• Equivariant score-based generative models provably learn distributions with symmetries efficiently
  di: Chen, Ziyu, et al.
  Pubblicazione: (2024)
• Statistical Guarantees of Group-Invariant GANs
  di: Chen, Ziyu, et al.
  Pubblicazione: (2023)
• Robust Generative Learning with Lipschitz-Regularized $α$-Divergences Allows Minimal Assumptions on Target Distributions
  di: Chen, Ziyu, et al.
  Pubblicazione: (2024)