3k citations · 8.1k across the 25 of their papers we have counts for
4 papers · 1 filter
Unrestricted Adversarial Examples
Tom B. Brown, Nicholas Carlini, Chiyuan Zhang +3
We introduce a two-player contest for evaluating the safety and robustness of machine learning systems, with a large prize pool. Unlike most prior work in ML robustness, which stud…
Skill Rating for Generative Models
Catherine Olsson, Surya Bhupatiraju, Tom Brown +2
We explore a new way to evaluate generative models using insights from evaluation of competitive games between human players. We show experimentally that tournaments between genera…
Is Generator Conditioning Causally Related to GAN Performance?
Augustus Odena, Jacob Buckman, Catherine Olsson +4
Recent work (Pennington et al, 2017) suggests that controlling the entire distribution of Jacobian singular values is an important design consideration in deep learning. Motivated…
Deep reinforcement learning from human preferences
Paul Christiano, Jan Leike, Tom B. Brown +3
For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we exp…