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Metalearned Neural Memory
Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang +1
We augment recurrent neural networks with an external memory mechanism that builds upon recent progress in metalearning. We conceptualize this memory as a rapidly adaptable functio…
Metalearning with Hebbian Fast Weights
Tsendsuren Munkhdalai, Adam Trischler
We unify recent neural approaches to one-shot learning with older ideas of associative memory in a model for metalearning. Our model learns jointly to represent data and to bind cl…
Synthesis of recurrent neural networks for dynamical system simulation
Adam Trischler, Gabriele MT D'Eleuterio
We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The alg…