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!
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 (nis 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!