6 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
Second-Order Neural ODE Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou
We propose a novel second-order optimization framework for training the emerging deep continuous-time models, specifically the Neural Ordinary Differential Equations (Neural ODEs).…
Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou
The connection between training deep neural networks (DNNs) and optimal control theory (OCT) has attracted considerable attention as a principled tool of algorithmic design. Despit…
A Differential Game Theoretic Neural Optimizer for Training Residual Networks
Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou
Connections between Deep Neural Networks (DNNs) training and optimal control theory has attracted considerable attention as a principled tool of algorithmic design. Differential Dy…
Neural Ordinary Differential Equations
Ricky T. Q. Chen, Yulia Rubanova, Jesse Bettencourt +1
We introduce a new family of deep neural network models. Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neur…
Isolating Sources of Disentanglement in Variational Autoencoders
Ricky T. Q. Chen, Xuechen Li, Roger Grosse +1
We decompose the evidence lower bound to show the existence of a term measuring the total correlation between latent variables. We use this to motivate our -TCVAE (Total Correla…