61 citations · 74 across the 3 of their papers we have counts for
3 papers
Robustifying Adversarial Training to the Union of Perturbation Models
Ameya D. Patil, Michael Tuttle, Alexander G. Schwing +1
Classical adversarial training (AT) frameworks are designed to achieve high adversarial accuracy against a single attack type, typically norm-bounded perturbations. R…
Compressing GANs using Knowledge Distillation
Angeline Aguinaldo, Ping-Yeh Chiang, Alex Gain +3
Generative Adversarial Networks (GANs) have been used in several machine learning tasks such as domain transfer, super resolution, and synthetic data generation. State-of-the-art G…
Shannon-inspired Statistical Computing to Enable Spintronics
Ameya D. Patil, Sasikanth Manipatruni, Dmitri Nikonov +2
Modern computing systems based on the von Neumann architecture are built from silicon complementary metal oxide semiconductor (CMOS) transistors that need to operate under practica…