no code implementations • ICLR 2018 • Chris Hettinger, Tanner Christensen, Jeffrey Humpherys, Tyler J. Jarvis
Due to the success of residual networks (resnets) and related architectures, shortcut connections have quickly become standard tools for building convolutional neural networks.
1 code implementation • 8 Jun 2017 • Chris Hettinger, Tanner Christensen, Ben Ehlert, Jeffrey Humpherys, Tyler Jarvis, Sean Wade
We present a general framework for training deep neural networks without backpropagation.
2 code implementations • 20 May 2017 • Kevin Miller, Chris Hettinger, Jeffrey Humpherys, Tyler Jarvis, David Kartchner
We present a general framework called forward thinking for deep learning that generalizes the architectural flexibility and sophistication of deep neural networks while also allowing for (i) different types of learning functions in the network, other than neurons, and (ii) the ability to adaptively deepen the network as needed to improve results.