Ibrahim Ayed - RankMe

22 papers A* 4Misc 1Journal 9Unranked 7

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Module-wise Training of Neural Networks via the Minimizing Movement Scheme. NeurIPS Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
2023	J	`jnl`	Module-wise Training of Neural Networks via the Minimizing Movement Scheme. CoRR Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
2022	A*	`conf`	A Neural Tangent Kernel Perspective of GANs. ICML Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
2022	—	`conf`	APHYN-EP: Physics-Based Deep Learning Framework to Learn and Forecast Cardiac Electrophysiology Dynamics. STACOM@MICCAI Victoriya Kashtanova, Mihaela Pop, Ibrahim Ayed, Patrick Gallinari, Maxime Sermesant
2022	—	`conf`	Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. MIDL Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant
2022	J	`jnl`	Modelling spatiotemporal dynamics from Earth observation data with neural differential equations. Mach. Learn. Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari
2022	J	`jnl`	Module-wise Training of Residual Networks via the Minimizing Movement Scheme. CoRR Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
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
2021	J	`jnl`	A Neural Tangent Kernel Perspective of GANs. CoRR Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
2021	A*	`conf`	Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting. ICLR Yuan Yin, Vincent Le Guen, Jérémie Donà, Emmanuel de Bézenac, Ibrahim Ayed, Nicolas Thome, Patrick Gallinari
2021	—	`conf`	CycleGAN Through the Lens of (Dynamical) Optimal Transport. ECML/PKDD (2) Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari
2021	—	`conf`	EP-Net 2.0: Out-of-Domain Generalisation for Deep Learning Models of Cardiac Electrophysiology. FIMH Victoriya Kashtanova, Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant
2021	A*	`conf`	LEADS: Learning Dynamical Systems that Generalize Across Environments. NeurIPS Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
2021	J	`jnl`	LEADS: Learning Dynamical Systems that Generalize Across Environments. CoRR Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
2021	—	`conf`	Learning Dynamical Systems across Environments. AAAI Spring Symposium: MLPS Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
2020	—	`conf`	A Principle of Least Action for the Training of Neural Networks. ECML/PKDD (2) Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
2020	J	`jnl`	A Principle of Least Action for the Training of Neural Networks. CoRR Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
2020	J	`jnl`	Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting. CoRR Vincent Le Guen, Yuan Yin, Jérémie Donà, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Thome, Patrick Gallinari
2020	Misc	`conf`	Learning the Spatio-Temporal Dynamics of Physical Processes from Partial Observations. ICASSP Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari
2019	—	`conf`	EP-Net: Learning Cardiac Electrophysiology Models for Physiology-Based Constraints in Data-Driven Predictions. FIMH Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant
2019	J	`jnl`	Learning Dynamical Systems from Partial Observations. CoRR Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari
2019	J	`jnl`	Optimal Unsupervised Domain Translation. CoRR Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari