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implementation of fGES (fast greedy equivalence search) #84

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huiouyang16 opened this issue Nov 1, 2022 · 2 comments
Open

implementation of fGES (fast greedy equivalence search) #84

huiouyang16 opened this issue Nov 1, 2022 · 2 comments

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@huiouyang16
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Does this repo have plans to implement the algorithm fGES[1]? fGES seems to work well for large scale problems. I wanna do some work on a large scale problem. If there is a related plan, it will help to use fGES more conveniently on the python platform, instead of calling Tetrad implemented in Java.

[1] Ramsey J, Glymour M, Sanchez-Romero R, et al. A million variables and more: the fast greedy equivalence search algorithm for learning high-dimensional graphical causal models, with an application to functional magnetic resonance images[J]. International journal of data science and analytics, 2017, 3(2): 121-129.

@kunwuz
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kunwuz commented Nov 1, 2022

Thanks for reaching out. Yes, we do have the plan to implement fGES on python, but it's still in its early stage. Please let me know if you (or/and anyone) would like to contribute. We are more than grateful for any help that benefits the community :)

@huiouyang16
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Thanks for reaching out. Yes, we do have the plan to implement fGES on python, but it's still in its early stage. Please let me know if you (or/and anyone) would like to contribute. We are more than grateful for any help that benefits the community :)

Yeah, of course I would like to do some related work. But I'm not sure if it can be done well since my current knowledge of fGES is limited. I'm willing to give it a shot, but may need some help along the way.

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