1 citations · 1 across the 3 of their papers we have counts for
3 papers
Heterogeneous Time Constants Improve Stability in Equilibrium Propagation
Yoshimasa Kubo, Suhani Pragnesh Modi, Smit Patel
Equilibrium propagation (EP) is a biologically plausible alternative to backpropagation for training neural networks. However, existing EP models use a uniform scalar time step dt,…
Toward Lifelong Learning in Equilibrium Propagation: Sleep-like and Awake Rehearsal for Enhanced Stability
Yoshimasa Kubo, Jean Erik Delanois, Maxim Bazhenov
Recurrent neural networks (RNNs) trained using Equilibrium Propagation (EP), a biologically plausible training algorithm, have demonstrated strong performance in various tasks such…
Biologically-inspired neuronal adaptation improves learning in neural networks
Yoshimasa Kubo, Eric Chalmers, Artur Luczak
Since humans still outperform artificial neural networks on many tasks, drawing inspiration from the brain may help to improve current machine learning algorithms. Contrastive Hebb…