Experimental characterization of the distribution of collagen fiber recruitment

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Publications associées (30)

Current propagation type self-consistent leader-return stroke model

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A current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel is described. The model takes into account the dispersion of the return stroke current along the return stroke channel. T ...

Elsevier2023

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

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Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Prateek Bansal, Thomas Gasos

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Compliance-matching vascular grafts with personalization potential

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Aortic diseases are characterized by dire prognosis and inadequate diagnosis, owing to their insidious yet lethal nature. Aortopathies, namely aortic aneurysms and dissections, along with certain congenital diseases, might necessitate surgical replacement ...

EPFL2023

Federated Learning under Covariate Shifts with Generalization Guarantees

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This paper addresses intra-client and inter-client covariate shifts in federated learning (FL) with a focus on the overall generalization performance. To handle covariate shifts, we formulate a new global model training paradigm and propose Federated Impor ...

2023

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Michael Christoph Gastpar, Aditya Pradeep

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

2023

Multi-scale characterization and modeling of notched strength and translaminar fracture in hybrid thin-ply composites based on different carbon fiber grades

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Owing to their high specific stiffness and strength, Carbon Fiber Reinforced Composites (CFRP) are ideal candidates for the development of lightweight high-performance structures. Within this family, thin-ply composites allow for wider design freedom and p ...

EPFL2023

Process development of pre-impregnated hybrid thin-ply composites

Alexios Argyropoulos

Thin-ply composites, obtained with recently developed fiber spreading techniques, rapidly gained industrial interest because they offer a large composite design freedom, and lead to a composite tensile strength that is close to that of the individual fiber ...

EPFL2023

Soft Multimaterial Magnetic Fibers and Textiles

Fabien Sorin, Syrine Mansour, Stella Andréa Françoise Laperrousaz, Chaoqun Dong, Andreas Leber, Hritwick Banerjee, Xue Wan, Rémi Andréa La Polla

Magnetically responsive soft materials are promising building blocks for the next generation of soft robotics, prosthesis, surgical tools, and smart textiles. To date, however, the fabrication of highly integrated magnetic fibers with extreme aspect ratios ...

Wiley-V C H Verlag Gmbh2023

Polynomial-time universality and limitations of deep learning

Emmanuel Abbé

The goal of this paper is to characterize function distributions that general neural networks trained by descent algorithms (GD/SGD), can or cannot learn in polytime. The results are: (1) The paradigm of general neural networks trained by SGD is poly-time ...

WILEY2023

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