178 citations · 306 across the 7 of their papers we have counts for
4 papers · 1 filter
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang +3
Adversarial purification refers to a class of defense methods that remove adversarial perturbations using a generative model. These methods do not make assumptions on the form of a…
Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds
Yujia Huang, Huan Zhang, Yuanyuan Shi +2
Certified robustness is a desirable property for deep neural networks in safety-critical applications, and popular training algorithms can certify robustness of a neural network by…
Neural Networks with Recurrent Generative Feedback
Yujia Huang, James Gornet, Sihui Dai +4
Neural networks are vulnerable to input perturbations such as additive noise and adversarial attacks. In contrast, human perception is much more robust to such perturbations. The B…
Out-of-Distribution Detection Using Neural Rendering Generative Models
Yujia Huang, Sihui Dai, Tan Nguyen +2
Out-of-distribution (OoD) detection is a natural downstream task for deep generative models, due to their ability to learn the input probability distribution. There are mainly two…