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Hey!
Thanks so much for your work!
I am working on the Allen Brain Observatory dataset and I was wondering can I use your package to fit Gabors to receptive fields of real neurons? ie say I use …
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Hi,
I am trying to interpret some impedance spectra using your package.
As a new user, I followed the procedure described in ``Fitting EIS data.ipynb'' and
I have successfully obtained the drt inv…
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def l0_norm(self, log_alpha, beta):
gamma = args.gamma
zeta = args.zeta
gamma = torch.tensor(gamma)
zeta = torch.tensor(zeta)
reg_per_weight = torch.sigmoid(log_alpha - beta * torch.log(-gam…
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Here is a proof of concept implementation by @agramfort
https://gist.github.com/1610922
Implementing this in the scikit would require a conversion to the scikit-learn API / naming conventions + …
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I have a custom forward operator defined as a sum of weighted convolutions to solve the `space-variant` deblurring problem. I am using `AcceleratedPGM` because of its fast convergence, as it doesn't r…
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I've been enforcing TV prior (1-norm of the gradient) in case of `ADMM` by supplying `L21Norm` as a functional in `g_list` and `FiniteDifference` as a math operator in `C_list`. However, since `ADMM` …
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# Problem
Need to devise the *initial approach* to designing the *class hierarchy* for `autoencoder`.
# Solution
Tentative *pseudo code* for what the class hierarchy might look like (including an…
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Hello, I cannot find the implementation of L0 regularization, which is mentioned in your paper. Could you please show me where it is?
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Hi! In your code you calculate the `Lc`
https://github.com/princeton-nlp/CoFiPruning/blob/main/trainer/trainer.py#L682
And you use `expected_size` to calculate `expected_sparsity` , but does i…