89 citations · 116 across the 4 of their papers we have counts for
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cs.LG2018★ 12 cited
Meta-learning autoencoders for few-shot prediction
Tailin Wu, John Peurifoy, Isaac L. Chuang +1
Compared to humans, machine learning models generally require significantly more training examples and fail to extrapolate from experience to solve previously unseen challenges. To…
cs.LG2017★ 14 cited
Gated Orthogonal Recurrent Units: On Learning to Forget
Li Jing, Caglar Gulcehre, John Peurifoy +4
We present a novel recurrent neural network (RNN) based model that combines the remembering ability of unitary RNNs with the ability of gated RNNs to effectively forget redundant/i…
cs.LG2016★ 89 cited
Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Li Jing, Yichen Shen, Tena Dubček +5
Using unitary (instead of general) matrices in artificial neural networks (ANNs) is a promising way to solve the gradient explosion/vanishing problem, as well as to enable ANNs to…