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20062021
most citedImproving Missing Data Imputation with Deep Generative Models

18 citations · 42 across the 12 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.CR20199 cited

A Data Science Approach for Honeypot Detection in Ethereum

Ramiro Camino, Christof Ferreira Torres, Mathis Baden +1

Ethereum smart contracts have recently drawn a considerable amount of attention from the media, the financial industry and academia. With the increase in popularity, malicious user…

cs.LG2019

SynGAN: Towards Generating Synthetic Network Attacks using GANs

Jeremy Charlier, Aman Singh, Gaston Ormazabal +2

The rapid digital transformation without security considerations has resulted in the rise of global-scale cyberattacks. The first line of defense against these attacks are Network…

cs.LG2019

Predicting Sparse Clients' Actions with CPOPT-Net in the Banking Environment

Jeremy Charlier, Radu State, Jean Hilger

The digital revolution of the banking system with evolving European regulations have pushed the major banking actors to innovate by a newly use of their clients' digital informatio…

cs.LG2019

PHom-GeM: Persistent Homology for Generative Models

Jeremy Charlier, Radu State, Jean Hilger

Generative neural network models, including Generative Adversarial Network (GAN) and Auto-Encoders (AE), are among the most popular neural network models to generate adversarial da…

cs.LG2019

Visualization of AE's Training on Credit Card Transactions with Persistent Homology

Jeremy Charlier, Francois Petit, Gaston Ormazabal +2

Auto-encoders are among the most popular neural network architecture for dimension reduction. They are composed of two parts: the encoder which maps the model distribution to a lat…

cs.LG2019

MQLV: Optimal Policy of Money Management in Retail Banking with Q-Learning

Jeremy Charlier, Gaston Ormazabal, Radu State +1

Reinforcement learning has become one of the best approach to train a computer game emulator capable of human level performance. In a reinforcement learning approach, an optimal va…