Boris Sobolev
@soboleffspaces
𝗦𝗰𝗵𝗼𝗹𝗮𝗿/𝗔𝘂𝘁𝗵𝗼𝗿/𝗧𝗲𝗮𝗰𝗵𝗲𝗿 • causality in plain language •
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And! Not only did causal theory @yudapearl lay the foundation for the “how” in mediation, fairness, and counterfactual analysis. It also gave us the “how” of Causal AI, opening the era of computable individual causal effects! In the process, it threw the regression…
Is it just me, or is “IRL-FAFO-headcanon” basically Pearl’s “seeing-doing-imagining” in Zoomer lingo? 🤭
If causal knowledge only comes from experiments or experience, then it just tells us how things happen, not how they have to be. But somehow, do-calculus and CTF-calculus manage to be pure reasoning, and still tell us what to expect in the real world.
Frank, a fair challenge in public space: a table in which causality concepts are expressed side by side in the language of DOE and SCM.
You are talking as though causal inference is opposing "experimental designs" etc. -- It isn't. Causal Inference is a language with which one can talk coherently and transparently about all aspect and cause-effect relationships.
The FDA framework for counterfactual estimands - what would have happened to the same patients had they been treated differently - is attempted with statistical machinery like outcome modeling, IPW, and principal strata. The problem is handling intercurrent events, i.e.,…
Implementation of the ICH E9 (R1) addendum in vaccine efficacy studies: the hypothetical and principal stratum strategies tandfonline.com/doi/full/10.10…
Well, ‘Freedom is the recognition of necessity’ is known at least since Hegel. 😊
"When we learn the laws of nature, how certain transformations are not possible, our freedom and potential actually increase, often dramatically so." ~Conjecture Institute Cofounder @astupple
In my #causality course, we spend a lot of time on the notion of a study unit: the real-world entity we intervene on and watch their response. Today I felt poetic: “In the beginning was the Unit. And the Unit was with Treatment, and with Outcome. And each possible Treatment…
Congratulations and thank you for your contribution to the field
My latest contribution to the theory of causal inference, just published in IJE; revisiting propensity scores (Rosenbaum and Rubin, 1983) and disease risk scores (Hansen, 2008) through the lens of causal diagrams (Pearl, 1995): academic.oup.com/ije/article-ab…
Hats off to @soboleffspaces, for bringing causal-ai to medicine. Calling for reforming @NIH's thinking. @NIHDirector_Jay @eliasbareinboim @murat_kocaoglu_ @pierreguyubc @hippysurgeon @JacobJHutton
🚀 Big milestone for our team! We’ve made our first real progress in implementing Causal AI, in the spirit of Pearl & Bareinboim’s SCM and DAG-informed training, to understand the causal effects of care standards in treating patients with hip fracture and to bring individualized…
What’s ahead is already now. Многая лѣта!
Conjecture Institute is honored to announce our second Advisor, computer scientist and philosopher @yudapearl! His books, including Causality and The Book of Why, have influenced fields ranging from epidemiology to economics.
The Guardian does a good job presenting the scientific challenge of linking paracetamol to autism. But the politically-motivated “mistrust” framing hides the sloppy research: • No causal diagram showing dependencies among factors that influence exposure and outcome. • No proven…
An intervention may help some and harm others—an idea conceptualized by @yudapearl at L3 of the causal hierarchy and further developed by @eliasbareinboim into counterfactual calculus.
A Columbia Mailman study provides the first human evidence linking #BreastCancer to a chemical compound once used as an anticancer drug. The research also shows how metabolomics can uncover hidden environmental risks and improve prediction in high-risk women.…
A Columbia Mailman study provides the first human evidence linking #BreastCancer to a chemical compound once used as an anticancer drug. The research also shows how metabolomics can uncover hidden environmental risks and improve prediction in high-risk women.…
Happy to share that it’s been an exciting season for our team with several NeurIPS papers accepted! These projects span causal representation learning, robust reinforcement learning, causal discovery, and interpretable modeling -- highlighting the development of causal…
A rare personal note. My dear friend Ivo (the dad) has a rare genetic liver disease (PSC) and has, after concerted persuasion from those of us who love him dearly, finally consented to a public appeal for a living donor. Liver donation is quite miraculous in that one can give…
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CAUSALab
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Judea Pearl
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