Full-Model Optimality for Tunable Linear Generative Priors in Compressed Sensing

arXiv:2609.02790 · stat.ML, cs.LG · Submitted 2026-09-02 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Reconstruction Error — 49× in this paper · explained in 2 episodes
• Generative Model — 22× in this paper · explained in 2 episodes
• Inverse Problem — 12× in this paper · explained in 2 episodes
• Generative Models — 9× in this paper · explained in 2 episodes
• AGN — 8× in this paper · explained in 1 episode
• Trace — 3× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Matrix Completion — 1× in this paper · explained in 4 episodes
• Non-asymptotic Analysis — 1× in this paper · explained in 2 episodes
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes

Sources

• Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems
• Introduction to the non-asymptotic analysis of random matrices

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