NeuSpin: Design of a Reliable Edge Neuromorphic System Based on Spintronics for Green AI

Autor: Ahmed, Soyed Tuhin, Danouchi, Kamal, Prenat, Guillaume, Anghel, Lorena, Tahoori, Mehdi B.

Internet of Things (IoT) and smart wearable devices for personalized healthcare will require storing and computing ever-increasing amounts of data. The key requirements for these devices are ultra-low-power, high-processing capabilities, autonomy at

Externí odkaz: http://arxiv.org/abs/2401.06195

Spatial-SpinDrop: Spatial Dropout-based Binary Bayesian Neural Network with Spintronics Implementation

Autor: Ahmed, Soyed Tuhin, Danouchi, Kamal, Hefenbrock, Michael, Prenat, Guillaume, Anghel, Lorena, Tahoori, Mehdi B.

Recently, machine learning systems have gained prominence in real-time, critical decision-making domains, such as autonomous driving and industrial automation. Their implementations should avoid overconfident predictions through uncertainty estimatio

Externí odkaz: http://arxiv.org/abs/2306.10185

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Scalable Spintronics-based Bayesian Neural Network for Uncertainty Estimation

Autor: Ahmed, Soyed Tuhin, Danouchi, Kamal, Hefenbrock, Michael, Prenat, Guillaume, Anghel, Lorena, Tahoori, Mehdi

Publikováno v: 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE)
2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), Apr 2023, Antwerp, Belgium. pp.1-6, ⟨10.23919/DATE56975.2023.10137167⟩

International audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3515::0cf359ab1b8aa2206aa7063c6441fee9
https://hal.science/hal-04148193

Binary Bayesian Neural Networks for Efficient Uncertainty Estimation Leveraging Inherent Stochasticity of Spintronic Devices

Autor: Tuhin, Soyed, Danouchi, Kamal, Münch, Christopher, Prenat, Guillaume, Anghel, Lorena, Tahoori, Mehdi, Neural, Bayesian

Publikováno v: 17th ACM International Symposium on Nanoscale Architectures
17th ACM International Symposium on Nanoscale Architectures, Association for Computing machinery, Dec 2022, Virtual conference, United States. ⟨10.1145/3565478.3572536⟩
NANOARCH '22: 17th ACM International Symposium on Nanoscale Architectures
NANOARCH '22: 17th ACM International Symposium on Nanoscale Architectures, Dec 2022, Virtual OR USA, United States. pp.1-6, ⟨10.1145/3565478.3572536⟩

International audience; In the age of automation, machine learning systems for real-time critical decisions in various domains such as autonomous driving are at an all-time high. Predictive uncertainty allows a machine learning system to make more in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8a93da4797cc86223f064f199400963
https://doi.org/10.1145/3565478.3572536