… One particular instantiation of a memory network is where the components are neural
networks. We refer to these as memory neural networks (MemNNs). In this section we describe a …

… a possibly large external memory. The architecture is a form of Memory Network [23] but …
For the former our approach is competitive with Memory Networks, but with less supervision. …

… -term memory/working memory networks is … memory, such as that of the mechanisms for
integrating different types of content (binding) or those providing the link to long-term memory. …

… For the rest of the paper, we will use the name memory network to describe any model which
has any form of these five components. We would like to highlight that all the components …

… memory tasks have revealed alterations in these networks in … alterations in these memory
networks even among cognitively … effects on these distributed memory circuits, even prior to …

… According to the views expressed in this article, memory networks are made by simultaneous
activation of neuronal assemblies representing external and internal events and inputs, …

… We introduce the dynamic memory network (DMN), a neural network architecture which
processes input sequences and questions, forms episodic memories, and generates relevant …

… -variable description of attractor networks. From this description … memory is large. The same
mean-field analysis also shows that the number of memories that can be stored in a network …

… dynamic user interest representations based on recurrent neural network (RNN). In DREAM,
all … In this work, however, we leverage user memory networks to store and manipulate each …

… memory network to adapt the template to the target’s appearance variations during tracking.
An LSTM is used as a memory … and writing process of the memory block. As the location of …