2 citations · 2 across the 3 of their papers we have counts for
4 papers
Pairwise Learning Increases Data Efficiency in Deep Neural Networks
Robert Bain, Marjan Rashidi, Elizabeth Chrastil
Deep neural networks often fail at small-sample regression, collapsing to low-variance predictions that miss individual differences. Here, we introduce a pairwise comparison framew…
The Role Of Biology In Deep Learning
Robert Bain
Artificial neural networks took a lot of inspiration from their biological counterparts in becoming our best machine perceptual systems. This work summarizes some of that history a…
Visualizing the Loss Landscape of Winning Lottery Tickets
Robert Bain
The underlying loss landscapes of deep neural networks have a great impact on their training, but they have mainly been studied theoretically due to computational constraints. This…
LossPlot: A Better Way to Visualize Loss Landscapes
Robert Bain, Mikhail Tokarev, Harsh Kothari +1
Investigations into the loss landscapes of deep neural networks are often laborious. This work documents our user-driven approach to create a platform for semi-automating this proc…