most citedKnow Your Model (KYM): Increasing Trust in AI and Machine Learning

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CY20212 cited

Know Your Model (KYM): Increasing Trust in AI and Machine Learning

Mary Roszel, Robert Norvill, Jean Hilger +1

The widespread utilization of AI systems has drawn attention to the potential impacts of such systems on society. Of particular concern are the consequences that prediction errors…

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…