29 citations · 73 across the 13 of their papers we have counts for
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cs.LG2019★ 2 cited
Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory
Kyle Helfrich, Qiang Ye
Several variants of recurrent neural networks (RNNs) with orthogonal or unitary recurrent matrices have recently been developed to mitigate the vanishing/exploding gradient problem…
cs.LG2019★ 1 cited
On regularization for a convolutional kernel in neural networks
Peichang Guo, Qiang Ye
Convolutional neural network is an important model in deep learning. To avoid exploding/vanishing gradient problems and to improve the generalizability of a neural network, it is d…
q-bio.BM2019★ 29 cited
Improving RNA secondary structure prediction via state inference with deep recurrent neural networks
Devin Willmott, David Murrugarra, Qiang Ye
The problem of determining which nucleotides of an RNA sequence are paired or unpaired in the secondary structure of an RNA, which we call RNA state inference, can be studied by di…