38 citations · 102 across the 11 of their papers we have counts for
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cs.HC2019
Ablate, Variate, and Contemplate: Visual Analytics for Discovering Neural Architectures
Dylan Cashman, Adam Perer, Remco Chang +1
Deep learning models require the configuration of many layers and parameters in order to get good results. However, there are currently few systematic guidelines for how to configu…
cs.LG2019★ 38 cited
RNNbow: Visualizing Learning via Backpropagation Gradients in Recurrent Neural Networks
Dylan Cashman, Genevieve Patterson, Abigail Mosca +3
We present RNNbow, an interactive tool for visualizing the gradient flow during backpropagation training in recurrent neural networks. RNNbow is a web application that displays the…