Questions tagged [interpolation]
5 questions
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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 of states and actions, and the transition…
Kostya
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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 specified by the ‘interpolation‘ argument set…
stoic-santiago
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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 state
Action($a_t$): Continuous multi-dimensional…
leodongxu
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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 interpolation adds no extra information to the input;…
MattSt
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How to interpret upsampling(deconv, nn, bilinear) as matrices?
I am reading this Distill article Deconvolution and Checkerboard Artifacts about avoiding artifacts in images generated by neural networks.
In the section of Better Upsampling, the author compares the difference between deconvolution (i.e.…
JonasW
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