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Publications associées (109)
A semantic model-based systems engineering approach for assessing the operational performance of metal forming process
Metal Forming is a basic and essential industrial process to provide materials for constructing complex products. To design an efficient metal forming process, the functional requirements and operational performance are two important aspects to be consider ...
Pergamon-Elsevier Science Ltd2024Robustness of Local Predictions in Atomistic Machine Learning Models
Michele Ceriotti, Federico Grasselli, Sanggyu Chong, Chiheb Ben Mahmoud
Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven si ...
Washington2023TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation
Jean-Philippe Thiran, Guillaume Marc Georges Vray, Devavrat Tomar
Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain. To tackle these issues, this paper proposes a novel Tes ...
IEEE2023Sampling of alternatives in migration aspiration models
Michel Bierlaire, Evangelos Paschalidis
The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...
2023Model-based Systems Engineering Papers Analysis based on Word Cloud Visualization
With the continuous improvement of system scale and complexity, model-based system engineering (MBSE) is of great importance in the practice of system engineering (SE). MBSE has been widely concerned in industry, especially in the field of complex equipmen ...
IEEE2022Physics Informed Neural Networks for Surrogate Modelling and Inverse Problems in Geotechnics
Finite elements methods (FEMs) have benefited from decades of development to solve partial differential equations (PDEs) and to simulate physical systems. In the recent years, machine learning (ML) and artificial neural networks (ANN) have shown great pote ...
2021Uncertainty-aware Model Inversion Networks
Romain Essy Théo Gratier De Saint-Louis
In this thesis, we assess a new framework called UMIN on a data-driven optimization problem. Such a problem happens recurrently in real life and can quickly become dicult to model when the input has a high dimensionality as images for instance. From the ar ...
2020Systems Engineering Approach to Identify Requirements for Digital Twins Development
Jinzhi Lu, Xiaochen Zheng, Ali Gharaei
Digital Twins (DT) are proposed in industries to support the entire lifecycle of services with different perspectives. Lack of systematic analysis of DT concepts leads to various definitions and services which challenges the DT developers for data integrat ...
SPRINGER INTERNATIONAL PUBLISHING AG2020Problem structuring to enable innovation in business/IT projects
Gil Regev, Tatiana Porté, Alain Wegmann
In this paper, we present a problem structuring method in business and IT analysis illustrated with an example. The project describes an IT consulting case done for a Swiss medical society faced with a problem of change management and digital transformatio ...
LUT Scientific and Expertise Publications2020