193 citations · 746 across the 16 of their papers we have counts for
4 papers · 1 filter
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick +1
In many applications, it is desirable to extract only the relevant information from complex input data, which involves making a decision about which input features are relevant. Th…
Been There, Done That: Meta-Learning with Episodic Recall
Samuel Ritter, Jane X. Wang, Zeb Kurth-Nelson +4
Meta-learning agents excel at rapidly learning new tasks from open-ended task distributions; yet, they forget what they learn about each task as soon as the next begins. When tasks…
On the importance of single directions for generalization
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz +1
Despite their ability to memorize large datasets, deep neural networks often achieve good generalization performance. However, the differences between the learned solutions of netw…
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study
Samuel Ritter, David G. T. Barrett, Adam Santoro +1
Deep neural networks (DNNs) have achieved unprecedented performance on a wide range of complex tasks, rapidly outpacing our understanding of the nature of their solutions. This has…