10.8k citations · 17.5k across the 28 of their papers we have counts for
6 papers · 1 filter
Plan, Attend, Generate: Planning for Sequence-to-Sequence Models
Francis Dutil, Caglar Gulcehre, Adam Trischler +1
We investigate the integration of a planning mechanism into sequence-to-sequence models using attention. We develop a model which can plan ahead in the future when it computes its…
Plan, Attend, Generate: Character-level Neural Machine Translation with Planning in the Decoder
Caglar Gulcehre, Francis Dutil, Adam Trischler +1
We investigate the integration of a planning mechanism into an encoder-decoder architecture with an explicit alignment for character-level machine translation. We develop a model t…
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…
Machine Comprehension by Text-to-Text Neural Question Generation
Xingdi Yuan, Tong Wang, Caglar Gulcehre +5
We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervis…
A Robust Adaptive Stochastic Gradient Method for Deep Learning
Caglar Gulcehre, Jose Sotelo, Marcin Moczulski +1
Stochastic gradient algorithms are the main focus of large-scale optimization problems and led to important successes in the recent advancement of the deep learning algorithms. The…
Memory Augmented Neural Networks with Wormhole Connections
Caglar Gulcehre, Sarath Chandar, Yoshua Bengio
Recent empirical results on long-term dependency tasks have shown that neural networks augmented with an external memory can learn the long-term dependency tasks more easily and ac…