SNaP one-step posterior sampling runs 30x faster than iterative samplers
prof_kamilov · x · 2026-09-29
SNaP from WashU performs one-step posterior sampling for inverse problems including deblurring, super-resolution, and inpainting. Each draw costs a single network evaluation, retains meaningful variation, and averaging multiple draws reduces pixel error. The thread shows comparisons against iterative reconstruction methods.
Related event: SNaP: One-Step Posterior Sampling Over 30x Faster Than Iterative Methods(3 posts)→
More from Multimodal
- Surflo (NeurIPS 2026 Oral) turns a handful of unposed photos into 3D surfaces, 10x faster — rsasaki0109 · 2026-09-29
- Finegrain Agentic Camera Demos Blazing Speed vs ChatGPT Image Processing — mattturck · 2026-09-29
- Wild video manipulation without ffmpeg: dev shows addictive new creative workflow — wavefnx · 2026-09-29
- Logolabs' Agate: 260M-Param Text-to-Image Model Trained in Just 145 GPU-Hours, MIT Licensed — linoy_tsaban · 2026-09-29
- Bonkers chase scene from AI film STAY HOME TOMORROW goes viral on Reddit — Western_Interview741 · 2026-09-29
- Community fix for Minimax H3 blurry faces: bump MMH3ultimate upscale steps to 2 — mwhjose · 2026-09-29