Search Results for author: Pierre-Edouard Portier

Found 6 papers, 4 papers with code

GRAN is superior to GraphRNN: node orderings, kernel- and graph embeddings-based metrics for graph generators

1 code implementation13 Jul 2023 Ousmane Touat, Julian Stier, Pierre-Edouard Portier, Michael Granitzer

We use these metrics to compare GraphRNN and GRAN, two well-known generative models for graphs, and unveil the influence of node orderings.

Drug Discovery Graph Embedding +2

PromptORE -- A Novel Approach Towards Fully Unsupervised Relation Extraction

1 code implementation24 Mar 2023 Pierre-Yves Genest, Pierre-Edouard Portier, Elöd Egyed-Zsigmond, Laurent-Walter Goix

We adapt the novel prompt-tuning paradigm to work in an unsupervised setting, and use it to embed sentences expressing a relation.

Relation Relation Extraction

Towards automated feature engineering for credit card fraud detection using multi-perspective HMMs

1 code implementation3 Sep 2019 Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Liyun He-Guelton, Olivier Caelen, Michael Granitzer, Sylvie Calabretto

Our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to improve the effectiveness of the classification task and allows for an increase in the detection of fraudulent transactions when combined with the state of the art expert based feature engineering strategy for credit card fraud detection.

Automated Feature Engineering Feature Engineering +1

Multiple perspectives HMM-based feature engineering for credit card fraud detection

1 code implementation15 May 2019 Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Olivier Caelen, Liyun He-Guelton, Sylvie Calabretto, Michael Granitzer

In this article, we model a sequence of credit card transactions from three different perspectives, namely (i) does the sequence contain a Fraud?

Feature Engineering Fraud Detection

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