183 citations · 185 across the 2 of their papers we have counts for
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cs.LG2016★ 2 cited
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks
Eder Santana, Matthew Emigh, Pablo Zegers +1
We propose a convolutional recurrent neural network, with Winner-Take-All dropout for high dimensional unsupervised feature learning in multi-dimensional time series. We apply the…
cs.LG2016★ 183 cited
Learning a Driving Simulator
Eder Santana, George Hotz
Comma.ai's approach to Artificial Intelligence for self-driving cars is based on an agent that learns to clone driver behaviors and plans maneuvers by simulating future events in t…
cs.LG2016
Information Theoretic-Learning Auto-Encoder
Eder Santana, Matthew Emigh, Jose C Principe
We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternativ…