14 citations · 19 across the 5 of their papers we have counts for
5 papers
A Dynamically Controlled Recurrent Neural Network for Modeling Dynamical Systems
Yiwei Fu, Samer Saab, Asok Ray +1
This work proposes a novel neural network architecture, called the Dynamically Controlled Recurrent Neural Network (DCRNN), specifically designed to model dynamical systems that ar…
Training products of expert capsules with mixing by dynamic routing
Michael Hauser
This study develops an unsupervised learning algorithm for products of expert capsules with dynamic routing. Analogous to binary-valued neurons in Restricted Boltzmann Machines, th…
Training capsules as a routing-weighted product of expert neurons
Michael Hauser
Capsules are the multidimensional analogue to scalar neurons in neural networks, and because they are multidimensional, much more complex routing schemes can be used to pass inform…
On Residual Networks Learning a Perturbation from Identity
Michael Hauser
The purpose of this work is to test and study the hypothesis that residual networks are learning a perturbation from identity. Residual networks are enormously important deep learn…
State Space Representations of Deep Neural Networks
Michael Hauser, Sean Gunn, Samer Saab +1
This paper deals with neural networks as dynamical systems governed by differential or difference equations. It shows that the introduction of skip connections into network archite…