2.1k citations · 3.3k across the 23 of their papers we have counts for
3 papers · 1 filter
Invertible Residual Networks
Jens Behrmann, Will Grathwohl, Ricky T. Q. Chen +2
We show that standard ResNet architectures can be made invertible, allowing the same model to be used for classification, density estimation, and generation. Typically, enforcing i…
Excessive Invariance Causes Adversarial Vulnerability
Jörn-Henrik Jacobsen, Jens Behrmann, Richard Zemel +1
Despite their impressive performance, deep neural networks exhibit striking failures on out-of-distribution inputs. One core idea of adversarial example research is to reveal neura…
i-RevNet: Deep Invertible Networks
Jörn-Henrik Jacobsen, Arnold Smeulders, Edouard Oyallon
It is widely believed that the success of deep convolutional networks is based on progressively discarding uninformative variability about the input with respect to the problem at…