1.8k citations · 2.4k across the 15 of their papers we have counts for
Showing 2017Show all
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cs.LG2017★ 57 cited
Twin Networks: Matching the Future for Sequence Generation
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni +3
We propose a simple technique for encouraging generative RNNs to plan ahead. We train a "backward" recurrent network to generate a given sequence in reverse order, and we encourage…
cs.NE2017★ 167 cited
Deep Complex Networks
Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang +7
At present, the vast majority of building blocks, techniques, and architectures for deep learning are based on real-valued operations and representations. However, recent work on r…