Department of Applied Mathematics, University of Washington, Seattle, WA, USA; Allen Institute for Brain Science, Seattle WA, USA; Computational Neuroscience Center, University of Washington, Seattle, WA, USA; School of Computer Science, McGill University, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada; Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC, Canada; Canada CIFAR AI Chair, CIFAR, Toronto, ON, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada; Canada CIFAR AI Chair, CIFAR, Toronto, ON, Canada; Dept. de Mathématiques et Statistiques, Université de Montréal, Montreal, QC, Canada; School of Computer Science, McGill University, Montreal, QC, Canada; Mila - Quebec AI Institute, Montreal, QC, Canada
Yuhan Helena Liu, Arna Ghosh, Blake Richards, Eric Shea-Brown, Guillaume Lajoie
Neuroscience;computational neuroscience;biologically plausible learning rules;learning and plasticity;temporal credit assignment;generalization;recurrent neural networks
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rules