1 citations · 1 across the 4 of their papers we have counts for
4 papers
Generative Binary Memory: Pseudo-Replay Class-Incremental Learning on Binarized Embeddings
Yanis Basso-Bert, Anca Molnos, Romain Lemaire +2
In dynamic environments where new concepts continuously emerge, Deep Neural Networks (DNNs) must adapt by learning new classes while retaining previously acquired ones. This challe…
Towards Experience Replay for Class-Incremental Learning in Fully-Binary Networks
Yanis Basso-Bert, Anca Molnos, Romain Lemaire +2
Binary Neural Networks (BNNs) are a promising approach to enable Artificial Neural Network (ANN) implementation on ultra-low power edge devices. Such devices may compute data in hi…
Scaling-up Memristor Monte Carlo with magnetic domain-wall physics
Thomas Dalgaty, Shogo Yamada, Anca Molnos +8
By exploiting the intrinsic random nature of nanoscale devices, Memristor Monte Carlo (MMC) is a promising enabler of edge learning systems. However, due to multiple algorithmic an…
Compositional Memory Systems for Multimedia Communicating Tasks
A. M. Molnos, M. J. M. Heijligers, S. D. Cotofana +1
Conventional cache models are not suited for real-time parallel processing because tasks may flush each other's data out of the cache in an unpredictable manner. In this way the sy…