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Internal reference : HSA
level0_domain_s : Computer Science [cs]
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Continuous Methods : Adaptively intrusive reduced order model closure

Emmanuel Menier , Michele Alessandro Bucci , Mouadh Yagoubi , Lionel Mathelin , Thibault Dairay , et al.
ICML 2022 - Workshop Continuous time methods for machine learning, Jul 2022, Baltimore, United States
Conference papers hal-03879332v1
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Deep Statistical Solvers

Balthazar Donon , Wenzhuo Liu , Antoine Marot , Zhengying Liu , Isabelle Guyon , et al.
NeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver / Virtuel, Canada
Conference papers hal-02974541v3
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Rail Crack Propagation Forecasting Using Multi-horizons RNNs

Sara Yasmine Ouerk , Olivier Vo Van , Mouadh Yagoubi
Advanced Analytics and Learning on Temporal Data | Workshop and Tutorial @ ECML-PKDD 2023, Sep 2023, Turin (Italie), Italy
Conference papers hal-04212352v1
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Multi-resolution Graph Neural Networks for PDE Approximation

Wenzhuo Liu , Mouadh Yagoubi , Marc Schoenauer
ICANN 2021 - 30th International Conference on Artificial Neural Networks, Sep 2021, Bratislava, Slovakia. pp.151-163, ⟨10.1007/978-3-030-86365-4_13⟩
Conference papers hal-03448278v1
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LIPS - Learning Industrial Physical Simulation benchmark suite

Milad Leyli-Abadi , David Danan , Mouadh Yagoubi , Seif-Eddine Attoui , Antoine Marot , et al.
NeurIPS - Data & Benchmark Track, Nov 2022, New Orleans, United States
Conference papers hal-03780816v1

Predictive analysis of fatigue crack growth on railroad tracks using machine learning techniques

Milad Leyli-Abadi , Olivier Vo Van
The Fifth International Conference on Railway Technology: Research, Development and Maintenance (Railways 2022), Aug 2022, Montpellier, France
Conference papers hal-03812030v1
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Continuous Methods : Hamiltonian Domain Translation

Emmanuel Menier , Michele Alessandro Bucci , Mouadh Yagoubi , Lionel Mathelin , Marc Schoenauer
Workshop « Continuous time methods for machine learning », ICML, Jul 2022, Baltimore, United States
Conference papers hal-03716629v1