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Found 3 papers, 1 papers with code
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing
Diffusion models have been leveraged to perform adversarial purification and thus provide both empirical and certified robustness for a standard model.
Performative Federated Learning: A Solution to Model-Dependent and Heterogeneous Distribution Shifts
We consider a federated learning (FL) system consisting of multiple clients and a server, where the clients aim to collaboratively learn a common decision model from their distributed data.
DensePure: Understanding Diffusion Models towards Adversarial Robustness
By using the highest density point in the conditional distribution as the reversed sample, we identify the robust region of a given instance under the diffusion model's reverse process.
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