Ibrahim Ayed

According to our database, Ibrahim Ayed authored at least 17 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Module-wise Training of Neural Networks via the Minimizing Movement Scheme.

Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

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).

Ibrahim Ayed

PhD thesis, 2022

Modelling spatiotemporal dynamics from Earth observation data with neural differential equations.

Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari

Mach. Learn., 2022

Module-wise Training of Residual Networks via the Minimizing Movement Scheme.

Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

CoRR, 2022

APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics.

Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant

Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

Deep Learning for Model Correction in Cardiac Electrophysiological Imaging.

Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

A Neural Tangent Kernel Perspective of GANs.

Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari

Proceedings of the International Conference on Machine Learning, 2022

2021

CycleGAN Through the Lens of (Dynamical) Optimal Transport.

Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

LEADS: Learning Dynamical Systems that Generalize Across Environments.

Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting.

Yuan Yin, Vincent Le Guen, Jérémie Donà, Emmanuel de Bézenac, Ibrahim Ayed, Nicolas Thome, Patrick Gallinari

Proceedings of the 9th International Conference on Learning Representations, 2021

EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology.

Victoriya Kashtanova, Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant

Proceedings of the Functional Imaging and Modeling of the Heart, 2021

Learning Dynamical Systems across Environments.

Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020

A Principle of Least Action for the Training of Neural Networks.

Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Learning the Spatio-Temporal Dynamics of Physical Processes from Partial Observations.

Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Optimal Unsupervised Domain Translation.

Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari

CoRR, 2019

Learning Dynamical Systems from Partial Observations.

Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari

CoRR, 2019

EP-Net: Learning Cardiac Electrophysiology Models for Physiology-Based Constraints in Data-Driven Predictions.

Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant

Proceedings of the Functional Imaging and Modeling of the Heart, 2019