Ibrahim Ayed

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 21

Top Topics

Partial Observations

Physical Processes

Top Venues

Publications

Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
Module-wise Training of Neural Networks via the Minimizing Movement Scheme. NeurIPS (2023)
Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
Module-wise Training of Neural Networks via the Minimizing Movement Scheme. CoRR (2023)
Victoriya Kashtanova, Ibrahim Ayed, Andony Arrieula, Mark Potse, Patrick Gallinari, Maxime Sermesant
Deep Learning for Model Correction in Cardiac Electrophysiological Imaging. MIDL (2022)
Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
A Neural Tangent Kernel Perspective of GANs. ICML (2022)
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)
Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations. Mach. Learn. 111 (6) (2022)
Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
Module-wise Training of Residual Networks via the Minimizing Movement Scheme. CoRR (2022)
Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
Learning Dynamical Systems across Environments. AAAI Spring Symposium: MLPS (2021)
Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
A Neural Tangent Kernel Perspective of GANs. CoRR (2021)
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)
Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
LEADS: Learning Dynamical Systems that Generalize Across Environments. CoRR (2021)
Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
LEADS: Learning Dynamical Systems that Generalize Across Environments. NeurIPS (2021)
Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari
CycleGAN Through the Lens of (Dynamical) Optimal Transport. ECML/PKDD (2) (2021)
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)
Vincent Le Guen, Yuan Yin, Jérémie Donà, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Thome, Patrick Gallinari
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting. CoRR (2020)
Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
A Principle of Least Action for the Training of Neural Networks. CoRR (2020)
Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari
Learning the Spatio-Temporal Dynamics of Physical Processes from Partial Observations. ICASSP (2020)
Skander Karkar, Ibrahim Ayed, Emmanuel de Bézenac, Patrick Gallinari
A Principle of Least Action for the Training of Neural Networks. ECML/PKDD (2) (2020)
Emmanuel de Bézenac, Ibrahim Ayed, Patrick Gallinari
Optimal Unsupervised Domain Translation. CoRR (2019)
Ibrahim Ayed, Nicolas Cedilnik, Patrick Gallinari, Maxime Sermesant
EP-Net: Learning Cardiac Electrophysiology Models for Physiology-Based Constraints in Data-Driven Predictions. FIMH (2019)
Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Julien Brajard, Patrick Gallinari
Learning Dynamical Systems from Partial Observations. CoRR (2019)