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I am wondering if you could give a hint on how to adjust he MDN layer to avoid weiging along the x-axis. Basically my dataset has many points on some regions for x-axis and I am only interested in fitting the data with weights along the y-axis.
Nealry all only examples show an "evenly" generated dataset for x and y, here the model will perform well.
Would you have any idea on how to skip weighing distribution along the x-axis and match the shape of distrubution for y? I was thinking of binning the data in zones of x and running sperate models only to combine them later.
Thanks !
The text was updated successfully, but these errors were encountered:
Hi there I have read your work, very good stuff.
I am wondering if you could give a hint on how to adjust he MDN layer to avoid weiging along the x-axis. Basically my dataset has many points on some regions for x-axis and I am only interested in fitting the data with weights along the y-axis.
Nealry all only examples show an "evenly" generated dataset for x and y, here the model will perform well.
Would you have any idea on how to skip weighing distribution along the x-axis and match the shape of distrubution for y? I was thinking of binning the data in zones of x and running sperate models only to combine them later.
Thanks !
The text was updated successfully, but these errors were encountered: