32 citations · 67 across the 12 of their papers we have counts for
3 papers · 1 filter
Neural networks with late-phase weights
Johannes von Oswald, Seijin Kobayashi, Alexander Meulemans +3
The largely successful method of training neural networks is to learn their weights using some variant of stochastic gradient descent (SGD). Here, we show that the solutions found…
A Theoretical Framework for Target Propagation
Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens +2
The success of deep learning, a brain-inspired form of AI, has sparked interest in understanding how the brain could similarly learn across multiple layers of neurons. However, the…
Continual Learning in Recurrent Neural Networks
Benjamin Ehret, Christian Henning, Maria R. Cervera +3
While a diverse collection of continual learning (CL) methods has been proposed to prevent catastrophic forgetting, a thorough investigation of their effectiveness for processing s…