228 citations · 1.4k across the 27 of their papers we have counts for
3 papers · 1 filter
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko, Pavel Izmailov, Andrew Gordon Wilson
Detecting out-of-distribution (OOD) data is crucial for robust machine learning systems. Normalizing flows are flexible deep generative models that often surprisingly fail to disti…
Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
Marc Finzi, Samuel Stanton, Pavel Izmailov +1
The translation equivariance of convolutional layers enables convolutional neural networks to generalize well on image problems. While translation equivariance provides a powerful…
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin +2
The loss functions of deep neural networks are complex and their geometric properties are not well understood. We show that the optima of these complex loss functions are in fact c…