96 citations
- Université Paris-SaclayFR6 papers
- CentraleSupélecFR4 papers
- Mathématiques et Informatique pour la Complexité et les Systèmes4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Département mathématiques, informatique, sciences de la donnée et technologies du numériqueFR2 papers
- Institut Polytechnique de ParisFR2 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR2 papers
- Laboratoire d'Ingénierie Circulation TransportsFR2 papers
- Laboratoire Interdisciplinaire des Sciences du NumériqueFR2 papers
- Safran (France)FR2 papers
- Sorbonne UniversitéFR2 papers
- Technical University of MunichDE2 papers
7 papers · 1 filter
Leveraging generative models to characterize the failure conditions of image classifiers
Adrien LeCoz, Stéphane Herbin, Faouzi Adjed
We address in this work the question of identifying the failure conditions of a given image classifier. To do so, we exploit the capacity of producing controllable distributions of…
Double-Logarithmic Depth Block-Encodings of Simple Finite Difference Method's Matrices
Sunheang Ty, Renaud Vilmart, Axel TahmasebiMoradi +1
Solving differential equations is one of the most computationally expensive problems in classical computing, occupying the vast majority of high-performance computing resources dev…
Graph Neural Network Approach to Predict the Effects of Road Capacity Reduction Policies: A Case Study for Paris, France
Elena Natterer, Roman Engelhardt, Sebastian Hörl +1
Rapid urbanization and growing urban populations worldwide present significant challenges for cities, including increased traffic congestion and air pollution. Effective strategies…
Regression under demographic parity constraints via unlabeled post-processing
Evgenii Chzhen, Mohamed Hebiri, Gayane Taturyan
We address the problem of performing regression while ensuring demographic parity, even without access to sensitive attributes during inference. We present a general-purpose post-p…
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design
Mouadh Yagoubi, David Danan, Milad Leyli-abadi +8
The integration of machine learning (ML) techniques for addressing intricate physics problems is increasingly recognized as a promising avenue for expediting simulations. However,…
Topological Analysis for Detecting Anomalies (TADA) in Time Series
Frédéric Chazal, Martin Royer, Clément Levrard
This paper introduces new methodology based on the field of Topological Data Analysis for detecting anomalies in multivariate time series, that aims to detect global changes in the…