17 citations · 29 across the 10 of their papers we have counts for
3 papers · 1 filter
Training Dynamical Binary Neural Networks with Equilibrium Propagation
Jérémie Laydevant, Maxence Ernoult, Damien Querlioz +1
Equilibrium Propagation (EP) is an algorithm intrinsically adapted to the training of physical networks, thanks to the local updates of weights given by the internal dynamics of th…
Synaptic metaplasticity in binarized neural networks
Axel Laborieux, Maxence Ernoult, Tifenn Hirtzlin +1
Unlike the brain, artificial neural networks, including state-of-the-art deep neural networks for computer vision, are subject to "catastrophic forgetting": they rapidly forget the…
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…