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09/20/2023
A representation-learning approach for insurance pricing with images
Unstructured data are a promising new source of information that insuran...
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12/16/2022
Reducing Sequence Length Learning Impacts on Transformer Models
Classification algorithms using Transformer architectures can be affecte...
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12/16/2022
Preventing RNN from Using Sequence Length as a Feature
Recurrent neural networks are deep learning topologies that can be train...
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12/07/2021
Multinational Address Parsing: A Zero-Shot Evaluation
Address parsing consists of identifying the segments that make up an add...
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04/26/2021
Geographic ratemaking with spatial embeddings
Spatial data is a rich source of information for actuarial applications:...
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02/11/2021
Rethinking Representations in P C Actuarial Science with Deep Neural Networks
Insurance companies gather a growing variety of data for use in the insu...
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11/24/2020
Generating Intelligible Plumitifs Descriptions: Use Case Application with Ethical Considerations
Plumitifs (dockets) were initially a tool for law clerks. Nowadays, they...
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06/29/2020
Leveraging Subword Embeddings for Multinational Address Parsing
Address parsing consists of identifying the segments that make up an add...
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12/14/2019
Attending Form and Context to Generate Specialized Out-of-VocabularyWords Representations
We propose a new contextual-compositional neural network layer that hand...
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12/03/2019
A Robust Self-Learning Method for Fully Unsupervised Cross-Lingual Mappings of Word Embeddings: Making the Method Robustly Reproducible as Well
In this paper, we reproduce the experiments of Artetxe et al. (2018b) re...
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03/02/2019
