1.3k citations · 2.9k across the 32 of their papers we have counts for
3 papers · 1 filter
Deep Prior
Alexandre Lacoste, Thomas Boquet, Negar Rostamzadeh +3
The recent literature on deep learning offers new tools to learn a rich probability distribution over high dimensional data such as images or sounds. In this work we investigate th…
Bayesian Hypernetworks
David Krueger, Chin-Wei Huang, Riashat Islam +3
We study Bayesian hypernetworks: a framework for approximate Bayesian inference in neural networks. A Bayesian hypernetwork $\h$ is a neural network which learns to transform a sim…
A Closer Look at Memorization in Deep Networks
Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas +8
We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noi…