Princeton University

CITP Lecture: Amanda Coston - Responsible Machine Learning through the Lens of Causal Inference

Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
insideHPC

Video Highlights: Machine Learning and Causal Inference

For our current edition of “Video Highlights” I’d like to offer this talk that will review a series of recent papers that develop new methods based on machine learning methods to approach problems of ...
Fred Hutch

Statistical Learning and Data Science Hub

Faculty in the Statistical Learning and Data Science Hub advance statistical and machine learning methods tailored to the unique challenges of biomedical and epidemiologic data, including ...

insitro Validates AI-Enabled POSH Platform in Nature Communications, Bridging Critical Gap in Drug Discovery

AI therapeutics company built on causal biology, today announced the publication of research in Nature Communications validating its POSH (Pooled Optical Screening in Human cells) platform. The study ...
JSTOR Daily

Commentary: On Two Approaches to Weighting in Causal Inference

Setodji CM, McCaffrey DF, Burgette LF, Almirall D, Griffin BA. The right tool for the job: Choosing between covariate balancing and generalized boosted model propensity scores. Epidemiology. 2017.
San Diego Reader

Rethinking Machine Learning: Stuart Frost Makes the Case for Causal AI in Manufacturing

The manufacturing landscape is evolving rapidly, with intelligent systems increasingly promising to boost efficiency, quality, and overall competitiveness. Traditional machine learning (ML) has ...