Questions tagged [interpolation]
The interpolation tag has no usage guidance.
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Is it possible to use a Neural Network to interpolate data [closed]
I am completely new to Artificial intelligence and Neural Networks. I am currently working on a plasma physics simulation project which requires a very high resolution data set. We currently have the ...
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How does the bigram terms are contributing to sophisticated version of linear interpolation?
While studying about linear interpolation technique in natural language processing to deal with less frequent $n-$gram. I came across a sophisticated version of linear interpolation.
The simple and ...
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63 views
Reward interpolation between MDPs. Will an optimal policy on both ends stay optimal inside the interval?
Say I've got two Markov Decision Processes (MDPs):
$$\mathcal{M_0} = (\mathcal{S}, \mathcal{A}, P, R_0),\quad\text{and}\quad\mathcal{M}_1 = (\mathcal{S}, \mathcal{A}, P, R_1)$$
Both have the same set ...
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NN for multivariate function interpolation
I have a multivariate function. It takes 4, real valued inputs: a, b, c, d and returns 1 complex number, z.
I wanted to use Neural Networks to predict the value z' for a generic input a', b', c', d'.
...
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139 views
What's the nearest neighbor algorithm used for upsampling?
Additionally, by default, the UpSampling2D layer will use a nearest neighbor algorithm to fill in the new rows and columns. This has the effect of simply doubling rows and columns, as described and is ...
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1answer
87 views
Continuous state and continuous action Markov decision process time complexity estimate: backward induction VS policy gradient method (RL)
Model Description: Model based(assume known of the entire model) Markov decision process.
Time($t$): Finite horizon discrete time with discounting factor
State($x_t$): Continuous multi-dimensional ...
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1answer
34 views
Interpolating image to increase resolution before feeding it to a neural network
Interpolation is a common way to make an image fit the right input shape for a neural network.
But is there any point in using interpolation to make it easier for the network to learn?
I assume ...
