Yujia Zheng

Yes, you are totally right. At the same time, regarding some tests, the theoretical guarantees might not hold when being performed in a parallel manner. Please feel free to let...

Thanks for letting us know. We will look into this. Meanwhile, if possible, could you please share a minimal code and sample dataset that could reproduce that issue?

Hi, we have updated our code (https://github.com/cmu-phil/causal-learn/pull/58). We believe it's related to the original data, which might not satisfy the assumption of the singularity of its covariance matrix, so we...

Hi, unfortunately, we don't have the functionality you described for now. We're not sure about the custom changes now, but we will try and see whether it's plausible.

> Thanks for the awesome work, @zhi-yi-huang !!!! This is great and really non-trivial, you fixed a tons of bugs that makes the package significantly better! > > One final...

Hi all, since this PR has already been for a while, please let me know if there is anything else before we can merge this.

Yeah, this is definitely something on the list. We will improve the APIs shortly. Thanks for your suggestion!

Yea, this is due to some violation of the data-generating process, e.g., violation of faithfulness. I don't know if any strategy exists to detect this given an observed dataset. The...

Perhaps adding some small random noises could help?

No, it hasn't yet included the rules introduced in Jiji's paper.