For questions related to reservoir computing (RC), which studies neural networks that are based on the concept of a reservoir.
Questions tagged [reservoir-computing]
4 questions
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What are examples of machine learning techniques inspired by neuroscience?
What are examples of machine learning techniques (i.e. models, algorithms, etc.) inspired (to different extents) by neuroscience?
Particularly, I'm interested in recent developments, say less than 10 years old, that have their basis in neuroscience…
SpiderRico
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Why do training and fixing a reservoir yield very similar results (in an echo state network)?
Disclaimer: I asked this question 2 days ago in Cross Validated, but it has been left unanswered.
I am trying to better understand how echo state networks work. To see, how fixing the weights of the reservoir of an echo state network impacts the…
User
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What are Reservoir computers used for today?
Reservoir computers were very popular in the early 2000s. From what I understand, the advantage of reservoir computers is that, as opposed to generic recurrent neural networks, training is only done on the linear output layer, making them much…
Nathaël
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What do echo state networks give us over a generic RNN resevoir?
Slightly generalizing the definition in Jaeger 2001, let's define a reservoir system to be any system of the form
$$h_{t}=f(h_{t-1}, x_t)$$
$$y_t=g(Wh_t)$$
where $f$ and $g$ are fixed and $W$ is a learnable weight matrix. The idea is we feed a…
Jack M
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