Thomas Mesquida

According to our database, Thomas Mesquida authored at least 13 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Are SNNs Really More Energy-Efficient Than ANNs? an In-Depth Hardware-Aware Study.

Manon Dampfhoffer, Thomas Mesquida, Alexandre Valentian, Lorena Anghel

IEEE Trans. Emerg. Top. Comput. Intell., June, 2023

Scaling-up Memristor Monte Carlo with magnetic domain-wall physics.

Thomas Dalgaty, Shogo Yamada, Anca Molnos, Eiji Kawasaki, Thomas Mesquida, François Rummens, Tatsuo Shibata, Yukihiro Urakawa, Yukio Terasaki, Tomoyuki Sasaki, Marc Duranton

CoRR, 2023

Improving the Robustness of Neural Networks to Noisy Multi-Level Non-Volatile Memory-based Synapses.

Manon Dampfhoffer, Joel Minguet Lopez, Thomas Mesquida, Alexandre Valentian, Lorena Anghel

Proceedings of the International Joint Conference on Neural Networks, 2023

Leveraging Sparsity with Spiking Recurrent Neural Networks for Energy-Efficient Keyword Spotting.

Manon Dampfhoffer, Thomas Mesquida, Emmanuel Hardy, Alexandre Valentian, Lorena Anghel

Proceedings of the IEEE International Conference on Acoustics, 2023

The CNN vs. SNN Event-camera Dichotomy and Perspectives For Event-Graph Neural Networks.

Thomas Dalgaty, Thomas Mesquida, Damien Joubert, Amos Sironi, Cyrille Soubeyrat, Pascal Vivet, Christoph Posch

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

HUGNet: Hemi-Spherical Update Graph Neural Network applied to low-latency event-based optical flow.

Thomas Dalgaty, Thomas Mesquida, Damien Joubert, Amos Sironi, Pascal Vivet, Christoph Posch

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

G2N2: Lightweight Event Stream Classification with GRU Graph Neural Networks.

Thomas Mesquida, Manon Dampfhoffer, Thomas Dalgaty, Pascal Vivet, Amos Sironi, Christoph Posch

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Investigating Current-Based and Gating Approaches for Accurate and Energy-Efficient Spiking Recurrent Neural Networks.

Manon Dampfhoffer, Thomas Mesquida, Alexandre Valentian, Lorena Anghel

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving.

Sambit Mohapatra, Thomas Mesquida, Mona Hodaei, Senthil Kumar Yogamani, Heinrich Gotzig, Patrick Maeder

Proceedings of the 8th International Conference on Event-Based Control, 2022

2020

Fully-Integrated Spiking Neural Network Using SiOx-Based RRAM as Synaptic Device.

Amir Regev, Alessandro Bricalli, Giuseppe Piccolboni, Alexandre Valentian, Thomas Mesquida, Gabriel Molas, Jean-François Nodin

Proceedings of the 2nd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2020

2019

Spiking Neural Networks Hardware Implementations and Challenges: A Survey.

Maxence Bouvier, Alexandre Valentian, Thomas Mesquida, François Rummens, Marina Reyboz, Elisa Vianello, Edith Beigné

ACM J. Emerg. Technol. Comput. Syst., 2019

2017

Architecture exploration of a fixed point computation unit using precise timing spiking neurons.

Thomas Mesquida, Alexandre Valentian, David Bol, Edith Beigné

Proceedings of the 27th International Symposium on Power and Timing Modeling, 2017

2016

MCAPI-compliant Hardware Buffer Manager mechanism to support communication in multi-core architectures.

Thiago Raupp da Rosa, Thomas Mesquida, Romain Lemaire, Fabien Clermidy

Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016