Adam Li

Hey @robertness I'm going through the PRs and adding labels to organize our thoughts on what we need for a v0.1 release. I added labels for score-based, constraint-based and differentiable-based...

Here is a rendered doc that is a WIP of the PC algorithm API and its usage: https://output.circle-artifacts.com/output/job/4d057804-45d2-488b-89de-11fd8d37743c/artifacts/0/dev/index.html This base class also defines the interface for any "constraint" causal discovery...

From the call, it seems the action items are: - [ ] implement a notebook/script that calls causal-learn and gets GES working on some example - [ ] write a...

> LGTM. One comment. The CMI value that is calculated as follows: > > `val = hxyz - (hxz + hyz - hz).mean()` > > Doesn't this have an asymptotic...

> Another con regarding the "melting pot" of assumptions is that it would be quite difficult to know in general if all of the causal assumptions specified are even compatible...

For default options, I think it's best to work backwards from each "proposed algorithm" that we would support. Eg. GES, PC, FCI, LinGAM, etc. We should have some sensible defaults...

Adding some more links: - https://py-why.github.io/dowhy/v0.8/example_notebooks/gcm_supply_chain_dist_change.html - https://py-why.github.io/dowhy/v0.8/example_notebooks/rca_microservice_architecture.html

The results of the algorithm are typically a graph, so I would presume, we just need a nice short example doc showing how to compare graphs learned from different algos?...

My current codebase developing `dodiscover` and its unit tests do not show an error rn because I use `pywhy-graphs`, but yeah you're right... an issue for networkx integration. However, I...

@jaron-lee > Would this be the right place to include the knowledge tiers functionality that TETRAD currently has? E.g. I group variables into X groups, where variables in group i...