10 citations · 20 across the 4 of their papers we have counts for
5 papers
Fast Adaptation with Linearized Neural Networks
Wesley J. Maddox, Shuai Tang, Pablo Garcia Moreno +2
The inductive biases of trained neural networks are difficult to understand and, consequently, to adapt to new settings. We study the inductive biases of linearizations of neural n…
Improving Style Transfer with Calibrated Metrics
Mao-Chuang Yeh, Shuai Tang, Anand Bhattad +2
Style transfer methods produce a transferred image which is a rendering of a content image in the manner of a style image. We seek to understand how to improve style transfer. To d…
A Simple Recurrent Unit with Reduced Tensor Product Representations
Shuai Tang, Paul Smolensky, Virginia R. de Sa
idely used recurrent units, including Long-short Term Memory (LSTM) and the Gated Recurrent Unit (GRU), perform well on natural language tasks, but their ability to learn structure…
Quantitative Evaluation of Style Transfer
Mao-Chuang Yeh, Shuai Tang, Anand Bhattad +1
Style transfer methods produce a transferred image which is a rendering of a content image in the manner of a style image. There is a rich literature of variant methods. However, e…
Improved Style Transfer by Respecting Inter-layer Correlations
Mao-Chuang Yeh, Shuai Tang
A popular series of style transfer methods apply a style to a content image by controlling mean and covariance of values in early layers of a feature stack. This is insufficient fo…