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Ibrahim Ayed
Ibrahim Ayed
Sorbonne Unviersité
Dirección de correo verificada de lip6.fr
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Año
AUGMENTING PHYSICAL MODELS WITH DEEP NET-WORKS FOR COMPLEX DYNAMICS FORECASTING
Y Yin, V Le Guen, J Dona, E de Bézenac, I Ayed, N Thome, P Gallinari
177*
Learning dynamical systems from partial observations
I Ayed, E de Bézenac, A Pajot, J Brajard, P Gallinari
arXiv preprint arXiv:1902.11136, 2019
992019
LEADS: Learning dynamical systems that generalize across environments
Y Yin, I Ayed, E de Bézenac, N Baskiotis, P Gallinari
Advances in Neural Information Processing Systems 34, 7561-7573, 2021
342021
CycleGAN Through the Lens of (Dynamical) Optimal Transport
E Bézenac, I Ayed, P Gallinari
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021
26*2021
Learning the spatio-temporal dynamics of physical processes from partial observations
I Ayed, E De Bezenac, A Pajot, P Gallinari
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
25*2020
A neural tangent kernel perspective of gans
JY Franceschi, E De Bézenac, I Ayed, M Chen, S Lamprier, P Gallinari
International Conference on Machine Learning, 6660-6704, 2022
232022
Ep-net: Learning cardiac electrophysiology models for physiology-based constraints in data-driven predictions
I Ayed, N Cedilnik, P Gallinari, M Sermesant
Functional Imaging and Modeling of the Heart: 10th International Conference …, 2019
162019
EP-Net 2.0: Out-of-domain generalisation for deep learning models of cardiac electrophysiology
V Kashtanova, I Ayed, N Cedilnik, P Gallinari, M Sermesant
International Conference on Functional Imaging and Modeling of the Heart …, 2021
152021
A Principle of Least Action for the Training of Neural Networks
S Karkar, I Ayed, E de Bézenac, P Gallinari
ECML 2020, 2020
132020
Deep Learning for Model Correction in Cardiac Electrophysiological Imaging
V Kashtanova, I Ayed, A Arrieula, M Potse, P Gallinari, M Sermesant
International Conference on Medical Imaging with Deep Learning, 665-675, 2022
11*2022
Learning dynamical systems from partial observations. CoRR abs/1902.11136 (2019)
I Ayed, E de Bézenac, A Pajot, J Brajard, P Gallinari
51902
Simultaneous data assimilation and cardiac electrophysiology model correction using differentiable physics and deep learning
V Kashtanova, M Pop, I Ayed, P Gallinari, M Sermesant
Interface Focus 13 (6), 20230043, 2023
42023
Module-wise Training of Neural Networks via the Minimizing Movement Scheme
S Karkar, I Ayed, E de Bézenac, P Gallinari
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023
22023
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations
I Ayed, E de Bézenac, A Pajot, P Gallinari
Machine Learning 111 (6), 2349-2380, 2022
22022
Block-wise Training of Residual Networks via the Minimizing Movement Scheme
S Karkar, I Ayed, E de Bézenac, P Gallinari
1st International Workshop on Practical Deep Learning in the Wild at 26th …, 2022
12022
Neural Models for Learning Real World Dynamics and the Neural Dynamics of Learning
I Ayed
Sorbonne université, 2022
2022
Learning Real World Dynamics with Neural Models and the Neural Dynamics of Learning
I Ayed
LEADS: Learning Dynamical Systems that Generalize Across Environments Supplemental Material
Y Yin, I Ayed, E de Bézenac, N Baskiotis, P Gallinari
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Artículos 1–18