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Hi, I've been reading your article recently and been very interested in your research. Your research is very prospective. I'd like to know more about it. The Python version of the code is better for me. Thank you. Please expose the code as soon as possible.

I am very interested in your work and I would like to regenerate the results on my data. A python version is the most suitable for me. Any date of release fixed yet?

I am trying to reproduce demo with cub-200-2011 dataset.

readAnnotation tries to open two files that are not part of dataset: image_class_labels.txt and train_test_split.txt

Could you please share the files or the code to create them?

Looking forward to your comments

Hi:
I saw author has realized the method to achieve the visualization of the filters，I want to know if it is the method in drawRF,please share shis to me, thank you !

Hi,

I am currently trying to recreate the results in the paper. However, I am unclear on why the mask array is flipped along the batch and filter dimension using END : -1 : 1 in backpropagation. I would appreciate if you could elaborate a bit on why this is done :)

Hi,

About computing p(x|T), the technique currently listed in the paper is wrong:

It's clear that you are trying to normalize all scores in a batch using softmax where score function is the sum over masked activations, i.e.,

however the trace operation is not correct, since it would end in

Please consider the modification - it might be a minor mistake however resulting in unnecessary confusion.

Hi, Could you please give more information on how to run demo.m. I have never used matlab, so it would be great if you could give an example of the commands used to train and test.

And , is it possible to execute this project on Octave.

Thanks

Error using vl_compilenn>check_clpath (line 599)
Unable to find cl.exe

Already tried mingw and visual studio 2019, both with matlab 2021b and CUDA 11

Would you please share the system specs in the following terms?

Matlab version
Visual studio version
MatConvNet 1.0 beta24 (known from code)
Cuda version

Any useful hint for setup is welcome!

Best regards!