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Teaser image to Generalized Data Thinning Using Sufficient Statistics

Colloquium

Generalized Data Thinning Using Sufficient Statistics

Jacob Bien, University of Southern California, LA

   12.06.2023

   3:00 pm - 4:30 pm

   LMU Department of Statistics and via zoom

Sample splitting, a common tool in data science, faces limitations. A recent method, convolution-closed data thinning, offers an alternative when sample splitting isn't feasible. This talk explores sufficiency as a key principle, leading to a unified framework called generalized data thinning.


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Link to Causal Inference Based on Machine Learning for Complex Longitudinal Exposures

Colloquium  •  12.11.2025  •  LMU Department of Statistics and via zoom

Causal Inference Based on Machine Learning for Complex Longitudinal Exposures

12.11.25, 4:15-5:45 pm: Iván Diaz and Herb Sussman from the New York University.


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