Questions about automatic-differentiation
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How can I fix this problem of automated differentiation with Tensorflow?
I need to compute the gradient wrt a loss for the variables of a defined neural network, the loss is computed correctly but the gradients are None. The code is the following:
variables = self.model.tr...
Giuseppe Boezio
Votes: 0
Answers: 1
automatic differentiation used on 'real dataset' settles in false minima why?
Hi so I've a done a project where we use tensorflow in automatic differentiation. Using a fairly linear dataset generated with numpy like so:
true_w, true_b = 7., 4.
def create_batch(batch_size=64)...
Brandyn Ewanek
Votes: 0
Answers: 1
How to pre-allocate space for intermediate computation values within DynamicAutoDiffCostFunction?
I am using Ceres Solver for the non-linear least squares optimization of a model for which the number of parameters is not known at compile time. Because the number of parameters is not known at compi...
user1158795
Votes: 0
Answers: 0
Julia JuMP making sure nonlinear objective function has correct function signatures so that autodifferentiate works properly?
so I wrote a minimum example to show what I'm trying to do. Basically I want to solve a optimization problem with multiple variables. When I try to do this in JuMP I was having issues with my function...
Eigenvalue
Votes: 0
Answers: 2