Pseudo-Invertible Neural Networks

arXiv:2602.06042 · cs.LG, cs.CV · Submitted 2026-02-05 · Read on arXiv

cs.LG, cs.CV

Submitted: 2026-02-05

Updated: 2026-09-25

Terminology

• Consistency — 20× in this paper · explained in 3 episodes
• Inverse Problem — 16× in this paper · explained in 2 episodes
• Non-Linear Back-Projection — 11× in this paper
• Diffusion Model — 6× in this paper · explained in 8 episodes
• Diffusion Process — 5× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Abstraction — 4× in this paper · explained in 1 episode
• Iterative Back-Projection — 3× in this paper
• Surjective Pseudo-invertible Neural Networks — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation study — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Non-linear Independent Components Estimation — 1× in this paper
• Normalizing Flow — 1× in this paper · explained in 3 episodes
• Normalizing Flows — 1× in this paper · explained in 4 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Generalized Inversion of Nonlinear Operators
• Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model
• Who Said Neural Networks Aren't Linear?
• NICE: Non-linear Independent Components Estimation

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