310 citations · 584 across the 20 of their papers we have counts for
3 papers · 1 filter
On 1/n neural representation and robustness
Josue Nassar, Piotr Aleksander Sokol, SueYeon Chung +2
Understanding the nature of representation in neural networks is a goal shared by neuroscience and machine learning. It is therefore exciting that both fields converge not only on…
Emergence of Separable Manifolds in Deep Language Representations
Jonathan Mamou, Hang Le, Miguel Del Rio +4
Deep neural networks (DNNs) have shown much empirical success in solving perceptual tasks across various cognitive modalities. While they are only loosely inspired by the biologica…
Untangling in Invariant Speech Recognition
Cory Stephenson, Jenelle Feather, Suchismita Padhy +4
Encouraged by the success of deep neural networks on a variety of visual tasks, much theoretical and experimental work has been aimed at understanding and interpreting how vision n…