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cs.LG2026
Training data attribution in diffusion models via mirrored unlearning and noise-consistent skew
Joan Serrà, Dipam Goswami, Fabio Morreale +2
Training data attribution (TDA) should enable generative model interpretability and foster a variety of related downstream tasks. Nonetheless, current TDA approaches lack reliabili…
cs.LG2024
Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Dipam Goswami, Simone Magistri, Kai Wang +3
Using pre-trained models has been found to reduce the effect of data heterogeneity and speed up federated learning algorithms. Recent works have explored training-free methods usin…