Search Results for author:
Found 3 papers, 1 papers with code
Visual Privacy Auditing with Diffusion Models
We propose a reconstruction attack based on diffusion models (DMs) that assumes adversary access to real-world image priors and assess its implications on privacy leakage under DP-SGD.
Bounding Reconstruction Attack Success of Adversaries Without Data Priors
When training ML models with differential privacy (DP), formal upper bounds on the success of such reconstruction attacks can be provided.
Fully Hyperbolic Convolutional Neural Networks for Computer Vision
To address this, we present HCNN, a fully hyperbolic convolutional neural network (CNN) designed for computer vision tasks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
