For questions related to the neural Turing machine model, proposed in "Neural Turing Machines" (2014) by Alex Graves et al.
Questions tagged [neural-turing-machine]
5 questions
13
votes
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How would DeepMind's new differentiable neural computer scale?
DeepMind just published a paper about a differentiable neural computer, which basically combines a neural network with a memory.
The idea is to teach the neural network to create and recall useful explicit memories for a certain task. This…
BlindKungFuMaster
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votes
2 answers
How much of Deep Mind's work is actually reproducible?
DeepMind has published a lot of works on deep learning in the last years, most of them are state-of-the-art on their respective tasks. But how much of this work has actually been reproduced by the AI community? For instance, the Neural Turing…
rcpinto
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How does the memory mechanism (reading and writing) work in a neural Turing machine?
In neural Turing machine (NTM), reading memory is represented as
\begin{align}
r_t \leftarrow \sum\limits_i^R w_t(i) \mathcal{M}_t(i) \tag{2}
\end{align}
and writing to memory is represented as
Step1: Erase
\begin{align}
\mathcal{M}_t^{erased}(i)…
Eka
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What is a location-based addressing in a neural Turing machine?
In the neural Turing machine (NTM), the content-based addressing and location-based addressing is used for memory addressing. Content-based addressing is similar to the attention-based model, weighting each row of memory which shows the importance…
eno
- 21
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votes
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Reasoning behind performance improvement with hopfield networks
In the paper Hopfield networks is all you need, the authors mention that their modern Hopfield network layers are a good replacement for pooling, GRU, LSTM, and attention layers, and tend to outperform them in various tasks.
I understand that they…
Rijul Gupta
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