353 citations · 631 across the 9 of their papers we have counts for
3 papers · 1 filter
Uncertainty in Multitask Transfer Learning
Alexandre Lacoste, Boris Oreshkin, Wonchang Chung +3
Using variational Bayes neural networks, we develop an algorithm capable of accumulating knowledge into a prior from multiple different tasks. The result is a rich and meaningful p…
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…
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…