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Ibrahim Ayed
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2020 – today
- 2023
- [c12]Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
Module-wise Training of Neural Networks via the Minimizing Movement Scheme. NeurIPS 2023 - [i8]Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
Module-wise Training of Neural Networks via the Minimizing Movement Scheme. CoRR abs/2309.17357 (2023) - 2022
- [b1]Ibrahim Ayed:
Neural Models for Learning Real World Dynamics and the Neural Dynamics of Learning. (Réseaux de neurones profonds pour la modélisation de phénomènes physiques complexes : incorporation de connaissances a priori). Sorbonne University, Paris, France, 2022 - [j1]Ibrahim Ayed
, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari:
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations. Mach. Learn. 111(6): 2349-2380 (2022) - [c11]Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari:
A Neural Tangent Kernel Perspective of GANs. ICML 2022: 6660-6704 - [c10]Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant:
Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. MIDL 2022: 665-675 - [c9]Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant:
APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics. STACOM@MICCAI 2022: 190-199 - [i7]Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
Module-wise Training of Residual Networks via the Minimizing Movement Scheme. CoRR abs/2210.00949 (2022) - 2021
- [c8]Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
Learning Dynamical Systems across Environments. AAAI Spring Symposium: MLPS 2021 - [c7]Victoriya Kashtanova, Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant:
EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology. FIMH 2021: 482-492 - [c6]Yuan Yin, Vincent Le Guen, Jérémie Donà, Emmanuel de Bézenac, Ibrahim Ayed, Nicolas Thome, Patrick Gallinari:
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting. ICLR 2021 - [c5]Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari:
LEADS: Learning Dynamical Systems that Generalize Across Environments. NeurIPS 2021: 7561-7573 - [c4]Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari:
CycleGAN Through the Lens of (Dynamical) Optimal Transport. ECML/PKDD (2) 2021: 132-147 - [i6]Yuan Yin
LEADS: Learning Dynamical Systems that Generalize Across Environments. CoRR abs/2106.04546 (2021) - [i5]Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari:
A Neural Tangent Kernel Perspective of GANs. CoRR abs/2106.05566 (2021) - 2020
- [c3]Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari:
Learning the Spatio-Temporal Dynamics of Physical Processes from Partial Observations. ICASSP 2020: 3232-3236 - [c2]Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
A Principle of Least Action for the Training of Neural Networks. ECML/PKDD (2) 2020: 101-117 - [i4]Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari:
A Principle of Least Action for the Training of Neural Networks. CoRR abs/2009.08372 (2020) - [i3]Vincent Le Guen, Yuan Yin
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting. CoRR abs/2010.04456 (2020)
2010 – 2019
- 2019
- [c1]Ibrahim Ayed
EP-Net: Learning Cardiac Electrophysiology Models for Physiology-Based Constraints in Data-Driven Predictions. FIMH 2019: 55-63 - [i2]Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari:
Learning Dynamical Systems from Partial Observations. CoRR abs/1902.11136 (2019) - [i1]Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari:
Optimal Unsupervised Domain Translation. CoRR abs/1906.01292 (2019)
Coauthor Index
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