[Re] Network Deconvolution

[rochanaro]

Original article: C. Ye, M. Evanusa, H. He, A. Mitrokhin, T. Goldstein, J. A. Yorke, C. Fermüller, and Y. Aloimonos. “Network
Deconvolution.” In: ICLR (2020).

PDF URL: https://github.com/lamps-lab/rep-network-deconvolution/blob/master/article.pdf
Metadata URL: https://github.com/lamps-lab/rep-network-deconvolution/blob/master/metadata.yaml
Code URL: https://github.com/lamps-lab/rep-network-deconvolution

Scientific domain: Machine Learning
Programming language: Python
Suggested editor:

[rougier]

Thanks for your submission. We'll assign an editor soon.

[rougier]

By the way is this submision part of the ICLR reproducibility challenge? If yes, are there any open review somewhere?

[rochanaro]

Thanks for your submission. We'll assign an editor soon.

Thank You!

[rochanaro]

By the way is this submision part of the ICLR reproducibility challenge? If yes, are there any open review somewhere?

No, our work was not submitted to ICLR reproducibility challenge.

[rougier]

Very sorry for such a long delay, hopefully things will get better for 2025.
I was asking the question because the format of the PDF is very similar to the ICLR challenge. Note that this is not a problem at all, the idea was to re-use review if they were available.

I'll edit your review and assign reviewers soon hopefully.

In the meantime, can you have a look at other submissions and propose yourself to review?

[rougier]

@birdortyedi @MiWeiss Coud lyou review this submission?

[rochanaro]

Very sorry for such a long delay, hopefully things will get better for 2025. I was asking the question because the format of the PDF is very similar to the ICLR challenge. Note that this is not a problem at all, the idea was to re-use review if they were available.

I'll edit your review and assign reviewers soon hopefully.

In the meantime, can you have a look at other submissions and propose yourself to review?

Thank you for the update! We understand how busy things can get.
Yes, for organizing the content, we tried to follow the structure of MLRC 2022 template only to ensure clarity.
I’ll certainly take a look at other submissions and will propose myself as a reviewer where I can contribute.

[MiWeiss]

Sounds like an interesting paper and a good match for me. Unfortunately, though, I won't be able to review a paper in the next months.

@rougier