6 citations · 8 across the 5 of their papers we have counts for
5 papers
Rethinking Representations in P&C Actuarial Science with Deep Neural Networks
Christopher Blier-Wong, Jean-Thomas Baillargeon, Hélène Cossette +2
Insurance companies gather a growing variety of data for use in the insurance process, but most traditional ratemaking models are not designed to support them. In particular, many…
Generating Intelligible Plumitifs Descriptions: Use Case Application with Ethical Considerations
David Beauchemin, Nicolas Garneau, Eve Gaumond +3
Plumitifs (dockets) were initially a tool for law clerks. Nowadays, they are used as summaries presenting all the steps of a judicial case. Information concerning parties' identity…
Attending Form and Context to Generate Specialized Out-of-VocabularyWords Representations
Nicolas Garneau, Jean-Samuel Leboeuf, Yuval Pinter +1
We propose a new contextual-compositional neural network layer that handles out-of-vocabulary (OOV) words in natural language processing (NLP) tagging tasks. This layer consists of…
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well
Nicolas Garneau, Mathieu Godbout, David Beauchemin +2
In this paper, we reproduce the experiments of Artetxe et al. (2018b) regarding the robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings. We…
Predicting and interpreting embeddings for out of vocabulary words in downstream tasks
Nicolas Garneau, Jean-Samuel Leboeuf, Luc Lamontagne
We propose a novel way to handle out of vocabulary (OOV) words in downstream natural language processing (NLP) tasks. We implement a network that predicts useful embeddings for OOV…