Research map / Image generation / Fast diffusion sampling
Normalizing Flows with Iterative Denoising
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Normalizing Flows are Capable Generative Models (ICML 2025 · similarity 0.94)
- Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling (ICLR 2026 · similarity 0.90)
- STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis (NeurIPS 2025 · similarity 0.89)
- Normalizing Trajectory Models (NeurIPS 2026 · similarity 0.89)
- Mean Flows for One-step Generative Modeling (NeurIPS 2025 · similarity 0.86)
- Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions (ICML 2025 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.