Dr. HE Jingyu (何靖宇)

Research Output

  1. 2019
  2. XBART: Accelerated Bayesian Additive Regression Trees

    He, J., Yalov, S. & Hahn, P. R., Apr 2019, The 22nd International Conference on Artificial Intelligence and Statistics. Chaudhuri, K. & Sugiyama, M. (eds.). PLMR, p. 1130-1138 (AISTATS - International Conference on Artificial Intelligence and Statistics)(Proceedings of Machine Learning Research; vol. 89).

    Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

    Scopus citations: 3
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  3. Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors

    Hahn, P. R., He, J. & Lopes, H. F., 2019, In: Journal of Computational and Graphical Statistics. 28, 1, p. 142-154

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 15
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  4. 2018
  5. Bayesian Factor Model Shrinkage for Linear IV Regression With Many Instruments

    Hahn, P. R., He, J. & Lopes, H., Apr 2018, In: Journal of Business and Economic Statistics. 36, 2, p. 278-287

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 6
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  6. Regularization and Confounding in Linear Regression for Treatment Effect Estimation

    Hahn, P. R., Carvalho, C. M., Puelz, D. & He, J., 2018, In: Bayesian Analysis. 13, 1, p. 163-182

    Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

    Scopus citations: 29
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