28 citations · 36 across the 4 of their papers we have counts for
7 papers
Ordered Memory
Yikang Shen, Shawn Tan, Arian Hosseini +3
Stack-augmented recurrent neural networks (RNNs) have been of interest to the deep learning community for some time. However, the difficulty of training memory models remains a pro…
Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery
Shawn Tan, Guillaume Androz, Ahmad Chamseddine +4
We release the largest public ECG dataset of continuous raw signals for representation learning containing 11 thousand patients and 2 billion labelled beats. Our goal is to enable…
Investigating Biases in Textual Entailment Datasets
Shawn Tan, Yikang Shen, Chin-wei Huang +1
The ability to understand logical relationships between sentences is an important task in language understanding. To aid in progress for this task, researchers have collected datas…
Improving Explorability in Variational Inference with Annealed Variational Objectives
Chin-Wei Huang, Shawn Tan, Alexandre Lacoste +1
Despite the advances in the representational capacity of approximate distributions for variational inference, the optimization process can still limit the density that is ultimatel…
Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikang Shen, Shawn Tan, Alessandro Sordoni +1
Natural language is hierarchically structured: smaller units (e.g., phrases) are nested within larger units (e.g., clauses). When a larger constituent ends, all of the smaller cons…
Generating Contradictory, Neutral, and Entailing Sentences
Yikang Shen, Shawn Tan, Chin-Wei Huang +1
Learning distributed sentence representations remains an interesting problem in the field of Natural Language Processing (NLP). We want to learn a model that approximates the condi…