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cs.LG2025
Kernel-Smoothed Scores for Denoising Diffusion: A Bias-Variance Study
Franck Gabriel, François Ged, Maria Han Veiga +1
Diffusion models now set the benchmark in high-fidelity generative sampling, yet they can, in principle, be prone to memorization. In this case, their learned score overfits the fi…
cs.LG2021★ 14 cited
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Şimşek, François Ged, Arthur Jacot +4
We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with layers of minimal wi…