Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions

Zeyuan Allen-Zhu, Yuanzhi Li
2/12/2026

No confident code implementation found for this paper. 2 possible matches can be shown below.

Semantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{allenzhu2026forward,
  title  = {Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions},
  author = {Zeyuan Allen-Zhu and Yuanzhi Li},
  year   = {2026},
  url    = {https://api.semanticscholar.org/CorpusID:276c91fc2f41f95bfd14ab003e70dcbd0656bfc1},
  journal = {ICLR 2023 2023}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/276c91fc2f41f95bfd14ab003e70dcbd0656bfc1.svg)](https://codeofpaper.com/paper/276c91fc2f41f95bfd14ab003e70dcbd0656bfc1)

Discussion