Taylor Pospisil

RFCDE: Random Forests for Conditional Density Estimation pdf

Ann B. Lee, Taylor Pospisil, 2018, ArXiv.

Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations

Rafael Izbicki, Ann B. Lee, Taylor Pospisil, 2019, AISTATS.

ABC–CDE: Toward Approximate Bayesian Computation With Complex High-Dimensional Data and Limited Simulations

Ann B. Lee, Rafael Izbicki, Taylor Pospisil, 2018, Journal of Computational and Graphical Statistics.

Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference

Rafael Izbicki, Ann B. Lee, Alex I. Malz, 2019 .

Going deep: models for continuous-time within-play valuation of game outcomes in American football with tracking data

Konstantinos Pelechrinis, Francesca Matano, Ronald Yurko, 2019 .

(f)RFCDE: Random Forests for Conditional Density Estimation and Functional Data

Ann B. Lee, Taylor Pospisil, T. Pospisil, 2019, 1906.07177.