278 citations · 286 across the 3 of their papers we have counts for
3 papers
Artificial Neuronal Ensembles with Learned Context Dependent Gating
Matthew J. Tilley, Michelle Miller, David J. Freedman
Biological neural networks are capable of recruiting different sets of neurons to encode different memories. However, when training artificial neural networks on a set of tasks, ty…
Learning Deep Generative Models with Annealed Importance Sampling
Xinqiang Ding, David J. Freedman
Variational inference (VI) and Markov chain Monte Carlo (MCMC) are two main approximate approaches for learning deep generative models by maximizing marginal likelihood. In this pa…
Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization
Nicolas Y. Masse, Gregory D. Grant, David J. Freedman
Humans and most animals can learn new tasks without forgetting old ones. However, training artificial neural networks (ANNs) on new tasks typically cause it to forget previously le…