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Dear developers, I am from a genomics background, but I would love to ask you one question regarding achieving super resolution for 3d data clouds of genomics datasets.
So say I have a 3d point cloud, each point has some features. I want to learn a smooth model of features from those 3D data points. Bascially a function (f) that map the spatial coordinates (x) to the features (y), say f(x) = y + n (n is the noise). I wonder whether this package can be adapted to this problem. Alternatively, if you can point me to the right direction, that will be awesome!
The text was updated successfully, but these errors were encountered:
Dear developers, I am from a genomics background, but I would love to ask you one question regarding achieving super resolution for 3d data clouds of genomics datasets.
So say I have a 3d point cloud, each point has some features. I want to learn a smooth model of features from those 3D data points. Bascially a function (
f
) that map the spatial coordinates (x
) to the features (y
), say f(x) = y + n (n
is the noise). I wonder whether this package can be adapted to this problem. Alternatively, if you can point me to the right direction, that will be awesome!The text was updated successfully, but these errors were encountered: