Working in Progress
- Bayesian Inference for Polya Inverse Gamma Models, with Chris Glynn, Nicholas Polson and Jianeng Xu.
- Deep Learning Particle Filtering, with Nicholas Polson and Yuexi Wang.
- Scalable Bayesian Tree-based Models for Supervised Machine Learning, with Saar Yalov, Jared Murray and P. Richard Hahn.
- Jingyu He, Saar Yalov and P. Richrad Hahn (2019). XBART: Accelerated Bayesian Additive Regression Trees. The 22nd International Conference on Artificial Intelligence and Statistics (AISTATS). slides, poster, package: XBART.
- P. Richrad Hahn, Jingyu He and Hedibert Lopes (2019). Efficient sampling for Gaussian linear regression with arbitrary priors. Journal of Computational and Graphical Statistics 28.1 (2019): 142-154. R package : bayeslm, Demo Script.
- P. Richard Hahn, Carlos M. Carvalho, Jingyu He and David Puelz (2018). Regularization and confounding in linear regression for treatment effect estimation. Bayesian Analysis 13 (1), 163-182.
- P. Richrad Hahn, Jingyu He and Hedibert Lopes (2018). Bayesian factor model shrinkage for linear IV regression with many instruments. Journal of Business and Economic Statistics 36 (2), 278-287.
20192019 China International Conference in Finance, Guangzhou.
2019 International Conference on FinTech, Shanghai Jiao Tong University.
NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics, Brown University.
China R Conference, Renmin University.
R in Finance, University of Illinois at Chicago.
Econometrics and Statistics Lunch Seminar, University of Chicago Booth School of Business.
2017Joint Statistical Meetings, Baltimore.
2016NBER-NSF Seminar on Bayesian Inference in Econometrics and Statistics, Wharton.
International Society of Bayesian Analysis World Meeting, Sardinia, Italy.