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2020 – today
- 2024
[j3]Manon Dampfhoffer
, Thomas Mesquida, Alexandre Valentian, Lorena Anghel:
Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11906-11921 (2024)- [c11]Manon Dampfhoffer, Thomas Mesquida:
Neuromorphic Lip-Reading with Signed Spiking Gated Recurrent Units. CVPR Workshops 2024: 2141-2151 - 2023
- [j2]Manon Dampfhoffer, Thomas Mesquida, Alexandre Valentian, Lorena Anghel:
Are SNNs Really More Energy-Efficient Than ANNs? an In-Depth Hardware-Aware Study. IEEE Trans. Emerg. Top. Comput. Intell. 7(3): 731-741 (2023) - [c10]Thomas Mesquida, Manon Dampfhoffer, Thomas Dalgaty, Pascal Vivet, Amos Sironi, Christoph Posch:
G2N2: Lightweight Event Stream Classification with GRU Graph Neural Networks. BMVC 2023: 660-663 - [c9]Thomas Dalgaty, Thomas Mesquida, Damien Joubert, Amos Sironi, Pascal Vivet, Christoph Posch:
HUGNet: Hemi-Spherical Update Graph Neural Network applied to low-latency event-based optical flow. CVPR Workshops 2023: 3953-3962 - [c8]Thomas Dalgaty, Thomas Mesquida, Damien Joubert, Amos Sironi, Cyrille Soubeyrat, Pascal Vivet, Christoph Posch:
The CNN vs. SNN Event-camera Dichotomy and Perspectives For Event-Graph Neural Networks. DATE 2023: 1-6 - [c7]Manon Dampfhoffer, Thomas Mesquida, Emmanuel Hardy, Alexandre Valentian, Lorena Anghel:
Leveraging Sparsity with Spiking Recurrent Neural Networks for Energy-Efficient Keyword Spotting. ICASSP 2023: 1-5 - [c6]Manon Dampfhoffer, Joel Minguet Lopez, Thomas Mesquida, Alexandre Valentian, Lorena Anghel:
Improving the Robustness of Neural Networks to Noisy Multi-Level Non-Volatile Memory-based Synapses. IJCNN 2023: 1-8 - [i3]Thomas Dalgaty, Shogo Yamada, Anca Molnos, Eiji Kawasaki, Thomas Mesquida, François Rummens, Tatsuo Shibata, Yukihiro Urakawa, Yukio Terasaki, Tomoyuki Sasaki, Marc Duranton:
Scaling-up Memristor Monte Carlo with magnetic domain-wall physics. CoRR abs/2312.02771 (2023) - 2022
- [c5]Sambit Mohapatra, Thomas Mesquida, Mona Hodaei, Senthil Kumar Yogamani, Heinrich Gotzig, Patrick Maeder:
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving. EBCCSP 2022: 1-5 - [c4]Manon Dampfhoffer, Thomas Mesquida, Alexandre Valentian, Lorena Anghel:
Investigating Current-Based and Gating Approaches for Accurate and Energy-Efficient Spiking Recurrent Neural Networks. ICANN (3) 2022: 359-370 - [i2]Sambit Mohapatra, Thomas Mesquida, Mona Hodaei, Senthil Kumar Yogamani, Heinrich Gotzig, Patrick Mäder:
SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving. CoRR abs/2206.02876 (2022) - 2020
- [c3]Amir Regev, Alessandro Bricalli, Giuseppe Piccolboni, Alexandre Valentian, Thomas Mesquida, Gabriel Molas, Jean-François Nodin:
Fully-Integrated Spiking Neural Network Using SiOx-Based RRAM as Synaptic Device. AICAS 2020: 145-148 - [i1]Maxence Bouvier, Alexandre Valentian, Thomas Mesquida, François Rummens, Marina Reyboz, Elisa Vianello, Edith Beigné:
Spiking Neural Networks Hardware Implementations and Challenges: a Survey. CoRR abs/2005.01467 (2020)
2010 – 2019
- 2019
- [j1]Maxence Bouvier, Alexandre Valentian, Thomas Mesquida, François Rummens, Marina Reyboz, Elisa Vianello, Edith Beigné:
Spiking Neural Networks Hardware Implementations and Challenges: A Survey. ACM J. Emerg. Technol. Comput. Syst. 15(2): 22:1-22:35 (2019) - 2017
- [c2]Thomas Mesquida, Alexandre Valentian, David Bol, Edith Beigné:
Architecture exploration of a fixed point computation unit using precise timing spiking neurons. PATMOS 2017: 1-8 - 2016
- [c1]Thiago Raupp da Rosa, Thomas Mesquida, Romain Lemaire, Fabien Clermidy:
MCAPI-compliant Hardware Buffer Manager mechanism to support communication in multi-core architectures. DATE 2016: 1006-1011
Coauthor Index
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