Difference between revisions of "Dist net.m"
| Line 4: | Line 4: | ||
==Syntax== | ==Syntax== | ||
| − | layers=dist_net( | + | layers=dist_net(np_in,np_out) |
==Arguments== | ==Arguments== | ||
| − | + | np_in - dimension of the input vector | |
| − | + | ||
| + | np_out - dimension of the output vector | ||
==Outputs== | ==Outputs== | ||
| Line 19: | Line 20: | ||
| − | ''Version 2. | + | ''Version 2.8, authors: [[Ilya Kuprov]], [[Jake Keeley]], [[Tajwar Choudhury]]'' |
Revision as of 10:18, 29 July 2023
Returns an untrained distance distribution DEERNet for processing fully sampled data.
Syntax
layers=dist_net(np_in,np_out)
Arguments
np_in - dimension of the input vector
np_out - dimension of the output vector
Outputs
layers - an untrained network layout
See also
Neural network module, deernet.m
Version 2.8, authors: Ilya Kuprov, Jake Keeley, Tajwar Choudhury
