175 citations · 376 across the 31 of their papers we have counts for
3 papers · 2 filters
Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations
Xing Chen, Flavio Abreu Araujo, Mathieu Riou +6
Deep learning has an increasing impact to assist research, allowing, for example, the discovery of novel materials. Until now, however, these artificial intelligence techniques hav…
Model of the Weak Reset Process in HfOx Resistive Memory for Deep Learning Frameworks
Atreya Majumdar, Marc Bocquet, Tifenn Hirtzlin +6
The implementation of current deep learning training algorithms is power-hungry, owing to data transfer between memory and logic units. Oxide-based RRAMs are outstanding candidates…
Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias
Axel Laborieux, Maxence Ernoult, Benjamin Scellier +3
Equilibrium Propagation (EP) is a biologically-inspired counterpart of Backpropagation Through Time (BPTT) which, owing to its strong theoretical guarantees and the locality in spa…