Mohamed Watfa

Identifiants chercheurs

IdHAL :

mohamed-watfa

ORCID :

0000-0003-4368-509X

Présentation

Publications

Article dans une revue (1)

Energy-based analog neural network framework Mohamed Watfa,Alberto Garcia-Ortiz,Gilles Sassatelli Frontiers in Computational Neuroscience, 2023, 17, ⟨10.3389/fncom.2023.1114651⟩ Article dans une revue lirmm-04306841v1

Communication dans un congrès (3)

Low-Rank Equilibrium Propagation: An Online Incremental Learning Architecture for Analog-Based Hardware Accelerators Mohamed Watfa,Alberto Garcia-Ortiz,Gilles Sassatelli MOCAST 2025 - 14th International Conference on Modern Circuits and Systems Technologies, Jun 2025, Dresden, Germany. ⟨10.1109/MOCAST65744.2025.11083959⟩ Communication dans un congrès hal-05098393v1
Designing Compatible Analog Circuits for Equilibrium Propagation: Implementations Using The Adjoint Method and Reciprocity Principles Mohamed Watfa,Alberto Garcia-Ortiz,Gilles Sassatelli ISVLSI 2025 - IEEE Computer Society Annual Symposium on VLSI, Jul 2025, Kalamata, Greece. pp.1-6, ⟨10.1109/ISVLSI65124.2025.11130216⟩ Communication dans un congrès lirmm-04959178v3
Energy-Based Analog Neural Network Framework Mohamed Watfa,Alberto Garcia-Ortiz,Gilles Sassatelli SOCC 2022 - 35th IEEE International System on Chip Conference, IEEE, Sep 2022, Belfast, United Kingdom. pp.1-6, ⟨10.1109/SOCC56010.2022.9908086⟩ Communication dans un congrès hal-03775570v1

Poster de conférence (1)

Efficient Edge AI Learning with Equilibrium Propagation: A Practical Solution For Gradient Computation Mohamed Watfa,Alberto Garcia-Ortiz,Gilles Sassatelli DAC 2026 - 63rd Design Automation Conference, Jul 2026, California, United States. Poster de conférence lirmm-04959185v2

Pré-publication, Document de travail (2)

Generative Replay for Equilibrium Propagation: Toward Edge-Friendly Continual Learning in Hopfield Networks Victor Cook,Gilles Sassatelli,Marina Reyboz,Thierry Gil,Mohamed Watfa 2026 Pré-publication, Document de travail lirmm-05525004v2
End-to-End Analog Edge AI Architecture For Scalable Energy-Efficient On-Chip Learning Mohamed Watfa,Gilles Sassatelli,Alberto Garcia-Ortiz 2024 Pré-publication, Document de travail lirmm-04660507v2