245 citations · 291 across the 5 of their papers we have counts for
5 papers
Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation
Melrose Roderick, Felix Berkenkamp, Fatemeh Sheikholeslami +1
In many real-world problems, there is a limited set of training data, but an abundance of unlabeled data. We propose a new method, Generative Posterior Networks (GPNs), that uses u…
Simple and Efficient Hard Label Black-box Adversarial Attacks in Low Query Budget Regimes
Satya Narayan Shukla, Anit Kumar Sahu, Devin Willmott +1
We focus on the problem of black-box adversarial attacks, where the aim is to generate adversarial examples for deep learning models solely based on information limited to output l…
Overfitting in adversarially robust deep learning
Leslie Rice, Eric Wong, J. Zico Kolter
It is common practice in deep learning to use overparameterized networks and train for as long as possible; there are numerous studies that show, both theoretically and empirically…
Deep Equilibrium Models
Shaojie Bai, J. Zico Kolter, Vladlen Koltun
We present a new approach to modeling sequential data: the deep equilibrium model (DEQ). Motivated by an observation that the hidden layers of many existing deep sequence models co…
Low-rank semidefinite programming for the MAX2SAT problem
Po-Wei Wang, J. Zico Kolter
This paper proposes a new algorithm for solving MAX2SAT problems based on combining search methods with semidefinite programming approaches. Semidefinite programming techniques are…