3.5k citations · 7.7k across the 28 of their papers we have counts for
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cs.LG2013★ 309 cited
Deep Generative Stochastic Networks Trainable by Backprop
Yoshua Bengio, Éric Thibodeau-Laufer, Guillaume Alain +1
We introduce a novel training principle for probabilistic models that is an alternative to maximum likelihood. The proposed Generative Stochastic Networks (GSN) framework is based…
cs.NE2013
Hands-free Evolution of 3D-printable Objects via Eye Tracking
Nick Cheney, Jeff Clune, Jason Yosinski +1
Interactive evolution has shown the potential to create amazing and complex forms in both 2-D and 3-D settings. However, the algorithm is slow and users quickly become fatigued. We…