5 citations · 9 across the 7 of their papers we have counts for
7 papers
FlowID : Enhancing Forensic Identification with Latent Flow-Matching Models
Jules Ripoll, David Bertoin, Alasdair Newson +2
Every day, many people die under violent circumstances, whether from crimes, war, migration, or climate disasters. Medico-legal and law enforcement institutions document many portr…
The Overfocusing Bias of Convolutional Neural Networks: A Saliency-Guided Regularization Approach
David Bertoin, Eduardo Hugo Sanchez, Mehdi Zouitine +1
Despite transformers being considered as the new standard in computer vision, convolutional neural networks (CNNs) still outperform them in low-data regimes. Nonetheless, CNNs ofte…
RRLS : Robust Reinforcement Learning Suite
Adil Zouitine, David Bertoin, Pierre Clavier +2
Robust reinforcement learning is the problem of learning control policies that provide optimal worst-case performance against a span of adversarial environments. It is a crucial in…
Time-Constrained Robust MDPs
Adil Zouitine, David Bertoin, Pierre Clavier +2
Robust reinforcement learning is essential for deploying reinforcement learning algorithms in real-world scenarios where environmental uncertainty predominates. Traditional robust…
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning
David Bertoin, Adil Zouitine, Mehdi Zouitine +1
Deep reinforcement learning policies, despite their outstanding efficiency in simulated visual control tasks, have shown disappointing ability to generalize across disturbances in…
Local Feature Swapping for Generalization in Reinforcement Learning
David Bertoin, Emmanuel Rachelson
Over the past few years, the acceleration of computing resources and research in deep learning has led to significant practical successes in a range of tasks, including in particul…
Disentanglement by Cyclic Reconstruction
David Bertoin, Emmanuel Rachelson
Deep neural networks have demonstrated their ability to automatically extract meaningful features from data. However, in supervised learning, information specific to the dataset us…