78 citations · 94 across the 10 of their papers we have counts for
5 papers · 1 filter
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux, Friedemann Zenke
Equilibrium propagation (EP) is a compelling alternative to the backpropagation of error algorithm (BP) for computing gradients of neural networks on biological or analog neuromorp…
Implicit variance regularization in non-contrastive SSL
Manu Srinath Halvagal, Axel Laborieux, Friedemann Zenke
Non-contrastive SSL methods like BYOL and SimSiam rely on asymmetric predictor networks to avoid representational collapse without negative samples. Yet, how predictor networks fac…
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations
Axel Laborieux, Friedemann Zenke
Equilibrium propagation (EP) is an alternative to backpropagation (BP) that allows the training of deep neural networks with local learning rules. It thus provides a compelling fra…
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…