Variable selection for Gaussian processes via sensitivity analysis of
the posterior predictive distribution

Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution

21 December 2017

Michael Riis Andersen

Papers citing "Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution"

5 / 5 papers shown

Title
Quantile-constrained Wasserstein projections for robust interpretability of numerical and machine learning models Marouane Il Idrissi Nicolas Bousquet Fabrice Gamboa Bertrand Iooss Jean-Michel Loubes 35 2 0 23 Sep 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 65 75 0 28 May 2022
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes Hugh Dance Brooks Paige GP 20 10 0 08 Nov 2021
Efficient Fourier representations of families of Gaussian processes P. Greengard 31 3 0 28 Sep 2021
Benchmarking the Performance of Bayesian Optimization across Multiple Experimental Materials Science Domains Qiaohao Liang Aldair E. Gongora Zekun Ren A. Tiihonen Zhe Liu ... K. Hippalgaonkar Benji Maruyama Keith A. Brown John W Fisher Iii Tonio Buonassisi 24 118 0 23 May 2021