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- Centre National de la Recherche ScientifiqueFR13 papers
- Institut national de recherche en sciences et technologies du numériqueFR10 papers
- Sorbonne UniversitéFR8 papers
- Laboratoire d'Informatique Gaspard-MongeFR7 papers
- Télécom ParisFR6 papers
- Centre de Robotique5 papers
- Institut de Recherche en Informatique et Systèmes AléatoiresFR5 papers
- Université Gustave EiffelFR5 papers
- Hôpital Saint-MichelFR4 papers
- Laboratoire d’Informatique et SystèmesFR4 papers
- Laboratoire Traitement et Communication de l’InformationFR4 papers
- Technicolor (France)FR4 papers
87 papers
AI- and Ontology-Based Enhancements to FMEA for Advanced Systems Engineering: Current Developments and Future Directions
Haytham Younus, Sohag Kabir, Felician Campean +2
This article presents a state-of-the-art review of recent advances aimed at transforming traditional Failure Mode and Effects Analysis (FMEA) into a more intelligent, data-driven,…
Improving Multimodal Distillation for 3D Semantic Segmentation under Domain Shift
Björn Michele, Alexandre Boulch, Gilles Puy +3
Semantic segmentation networks trained under full supervision for one type of lidar fail to generalize to unseen lidars without intervention. To reduce the performance gap under do…
Multiple-Frequencies Population-Based Training
Waël Doulazmi, Auguste Lehuger, Marin Toromanoff +3
Reinforcement Learning's high sensitivity to hyperparameters is a source of instability and inefficiency, creating significant challenges for practitioners. Hyperparameter Optimiza…
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
Armand Kassaï Koupaï, Jorge Mifsut Benet, Yuan Yin +2
Solving parametric partial differential equations (PDEs) presents significant challenges for data-driven methods due to the sensitivity of spatio-temporal dynamics to variations in…
Expected Improvement applied to an industrialcontext -- Prediction of new geometries increasing theefficiency of fans
Agnès Lagnoux, T. M. Ngoc Nguyen, Bruno Demory +1
In automotive industry, client needs evolve quickly in a competitiveness context, particularly, regarding the fan involved in the engine cooling module. This study has been done in…
CLIP's Visual Embedding Projector is a Few-shot Cornucopia
Mohammad Fahes, Tuan-Hung Vu, Andrei Bursuc +2
We introduce ProLIP, a simple and architecture-agnostic method for adapting contrastively pretrained vision-language models, such as CLIP, to few-shot classification. ProLIP fine-t…