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Hi,
Thanks for your great research. Does hash table work for second derivative with respect to x (input)? or it only works for weights?
for example, let say we have this sequence of passing info: x -> hash table -> neural network -> y
x -> hash table -> neural network -> y
Now I want to get the second partial derivative of y with respect to x (d2y/dx2).
Please let me know.
Thanks, Mehdi
The text was updated successfully, but these errors were encountered:
Hi, yes, this should be supported out of the box.
Importantly, you need to use
"interpolation": "Smoothstep",
when configuring the encoding. When using the default linear interpolation, the second derivative is always zero and hence not very useful.
Please feel free to re-open the issue if you discover a bug in this function.
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Hi,
Thanks for your great research. Does hash table work for second derivative with respect to x (input)? or it only works for weights?
for example, let say we have this sequence of passing info:
x -> hash table -> neural network -> y
Now I want to get the second partial derivative of y with respect to x (d2y/dx2).
Please let me know.
Thanks,
Mehdi
The text was updated successfully, but these errors were encountered: