18 citations · 42 across the 12 of their papers we have counts for
9 papers · 1 filter
Minority Class Oversampling for Tabular Data with Deep Generative Models
Ramiro Camino, Christian Hammerschmidt, Radu State
In practice, machine learning experts are often confronted with imbalanced data. Without accounting for the imbalance, common classifiers perform poorly and standard evaluation met…
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…
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…
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…
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…
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…