123 citations · 153 across the 6 of their papers we have counts for
8 papers
DS-GPS : A Deep Statistical Graph Poisson Solver (for faster CFD simulations)
Matthieu Nastorg, Marc Schoenauer, Guillaume Charpiat +3
This paper proposes a novel Machine Learning-based approach to solve a Poisson problem with mixed boundary conditions. Leveraging Graph Neural Networks, we develop a model able to…
DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification
Julien Girard-Satabin, Aymeric Varasse, Marc Schoenauer +2
The impressive results of modern neural networks partly come from their non linear behaviour. Unfortunately, this property makes it very difficult to apply formal verification tool…
Input Similarity from the Neural Network Perspective
Guillaume Charpiat, Nicolas Girard, Loris Felardos +1
We first exhibit a multimodal image registration task, for which a neural network trained on a dataset with noisy labels reaches almost perfect accuracy, far beyond noise variance.…
CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators
Julien Girard-Satabin, Guillaume Charpiat, Zakaria Chihani +1
The topic of provable deep neural network robustness has raised considerable interest in recent years. Most research has focused on adversarial robustness, which studies the robust…
Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data
Sophie Giffard-Roisin, Mo Yang, Guillaume Charpiat +3
The forecast of tropical cyclone trajectories is crucial for the protection of people and property. Although forecast dynamical models can provide high-precision short-term forecas…
Noisy Supervision for Correcting Misaligned Cadaster Maps Without Perfect Ground Truth Data
Nicolas Girard, Guillaume Charpiat, Yuliya Tarabalka
In machine learning the best performance on a certain task is achieved by fully supervised methods when perfect ground truth labels are available. However, labels are often noisy,…