17 citations · 17 across the 5 of their papers we have counts for
5 papers
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness
Jieren Deng, Hanbin Hong, Aaron Palmer +5
Randomized smoothing has become a leading method for achieving certified robustness in deep classifiers against l_{p}-norm adversarial perturbations. Current approaches for achievi…
Distilling Adversarial Robustness Using Heterogeneous Teachers
Jieren Deng, Aaron Palmer, Rigel Mahmood +4
Achieving resiliency against adversarial attacks is necessary prior to deploying neural network classifiers in domains where misclassification incurs substantial costs, e.g., self-…
The sharp interface limit of an Ising game
William M Feldman, Inwon C Kim, Aaron Zeff Palmer
The Ising model of statistical physics has served as a keystone example of phase transitions, thermodynamic limits, scaling laws, and many other phenomena and mathematical methods.…
Auto-Encoding Goodness of Fit
Aaron Palmer, Zhiyi Chi, Derek Aguiar +1
We develop a new type of generative autoencoder called the Goodness-of-Fit Autoencoder (GoFAE), which incorporates GoF tests at two levels. At the minibatch level, it uses GoF test…
VIGAN: Missing View Imputation with Generative Adversarial Networks
Chao Shang, Aaron Palmer, Jiangwen Sun +3
In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collect…