Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training
Separates the onset of useful diffusion generation from later training-data memorization. Experiments and a random-features model analyze how training dynamics create a window of generalization before memorization.
Overview
Separates the onset of useful diffusion generation from later training-data memorization. Experiments and a random-features model analyze how training dynamics create a window of generalization before memorization.
Separates the onset of useful diffusion generation from later training-data memorization. Experiments and a random-features model analyze how training dynamics create a window of generalization before memorization.
When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.
Separates the onset of useful diffusion generation from later training-data memorization. Experiments and a random-features model analyze how training dynamics create a window of generalization before memorization.
Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.
References
ID: neurips-2025-diffusion-dynamical-regularization · Last verified:
