And so, in this paper we revisit the meta-learning problem and setup from the perspective of a highly capable memory-augmented neural network (MANN) (note: here ...
We demonstrate the ability of a memory-augmented neural network to rapidly assimilate new data, and leverage this data to make accurate predictions after only ...
Oct 12, 2023 · The proposed memory-augmented neural network demonstrates the ability to rapidly assimilate new data and make accurate predictions after only a ...
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Jan 28, 2023 · The premise is that In some cases, we wish to perform meta-learning when we are only provided with small (or no) data.
This paper revisited the idea of meta-learning and proposed a new memory augmented neural network by explicitly splitting the external memory into feature ...
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May 19, 2016 · We demonstrate the ability of a memory-augmented neural network to rapidly assimilate new data, and leverage this data to make accurate predictions after only ...
May 10, 2020 · The idea of Meta Learning is that to allow a Neural Network to learn across previous tasks and to accomplish a new unseen task. Many researches ...
The authors attack the problem of one-shot learning by the approach of meta-learning. They propose Memory Augmented Neural Network, which is a variant of Neural ...
This paper classifies that previous model, the Neural Turing Machine (NTM), as a subclass of the more general class of Memory-Augmented Neural Networks (MANNs).
(2016) Meta-Learning with Memory-Augmented Neural Networks. Proceedings of the 33rd International Conference on Machine Learning, in PMLR 48, 1842-1850. has ...