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Anybody knows a course that includes some causal inference? I think the lack of focus on causal inference is pitty and even a mistake.
by cyrksoft 5y ago
Anybody knows a course that includes some causal inference? I think the lack of focus on causal inference is pitty and even a mistake.
- teruakohatu 5y agoIt is an introductory course, there is going to be a lot it does not cover.
- cyrksoft 5y agoI know it's an introductory course, that's why I was asking if anybody knew any course that did. And even if it is introductory, you need some previous knowledge to get to this course. I haven't found any CS curriculum that teaches causal inference in any way (maybe in optional courses, but that misses the point) and I think that it is a huge mistake. Causality is more important than simple prediction. I don't understand why CS people escape causality in most courses, not even mentioning it.
- missingsteps2 5y agoPerhaps using deep learning methods for bayesian neural networks (*) is very recent. Belief Networks in Modern AI chapter 19, section 6. https://www.nature.com/articles/s42256-020-0218-x https://www.nature.com/articles/s42256-020-0218-x
- buixuanquy 5y agoQuote from Statistical Rethinking: > We must keep in mind the lessons: Inferring cause and making predictions are different tasks. Models that are causally incorrect can make better predictions than those that are causally correct. Yes, it's a paradox.
- bvasilis 5y agoHere's a separate course titled "Introduction to causal inference (from a machine learning perspective)". It's from Brady Neal, who works in the group of Yoshua Bengio. https://www.bradyneal.com/causal-inference-course https://www.bradyneal.com/causal-inference-course
- g42gregory 5y agoI've been looking for a causal inference class myself. This looks like a very nice course, complete with video lectures. Thank you for posting this!
- huitzitziltzin 5y agoThere are economists who are working on ML and causal inference. I know of no courses but I can refer you to some papers... (These titles are from memory bc I am typing with one hand as I hold a sleeping infant with the other.) - taddy, et al “deep IV”. - Greg Lewis at Microsoft research has work here too... the title of that paper I cannot remember. - Farrell, Liang and Misra, “neural networks for estimation and inference” (econometrica 2021) - For non neural network based ml informed approaches to causal inference, victor chernozhukov, alexandre Belloni and Christian Hansen have a long series of papers going back to 2011 (sometimes with other coauthors) which are generally based on the LASSO in settings with many instrumental variables. - chernozhukov, demirer, duflo, et al have a paper on “double machine learning” which is relevant. I think there is relevant work in biostat by Jamie Robins, but that is not my field. - athey, imbens and wager have papers on random forest based approaches - at least one is in JASA. Might be called “causal forests” ? - since economists frequently estimate in the GMM (generalIzed method of moments, not Gaussian mixture model) framework, there is some recent work by... Kallus (?) on formulating GMM as an adversarial game. Greg lewis and V. Syrgkanis have also worked on this problem but the title of the paper escapes me. I would like to teach this material myself so there will one day be a class (inshallah) but so far have not had time to organize it yet!
- cyrksoft 5y agoThese look very interesting, thanks! If you every make a class out of it, please post it here!