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ORCIDRui Tuo 0001
Person information
- affiliation: Texas A&M University, Department of Industrial and Systems Engineering, College Station, TX, USA
- affiliation (PhD 2013): Chinese Academy of Sciences, Academy of Mathematics and Systems Science, Beijing, China
Other persons with the same name
- Rui Tuo 0002 — Shandong Institute of Non-metallic Materials, Jinan, China
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2020 – today
- 2025
[c4]Wenyuan Zhao, Haoyuan Chen, Tie Liu, Rui Tuo, Chao Tian:
From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation. AISTATS 2025: 4231-4239- [i12]Wenyuan Zhao, Haoyuan Chen, Tie Liu, Rui Tuo, Chao Tian:
From Deep Additive Kernel Learning to Last-Layer Bayesian Neural Networks via Induced Prior Approximation. CoRR abs/2502.10540 (2025) - 2024
- [j16]Gecheng Chen
, Yu Zhou, Xudong Zhang, Rui Tuo:
Renewing Iterative Self-Labeling Domain Adaptation With Application to the Spine Motion Prediction. IEEE Trans Autom. Sci. Eng. 21(3): 3543-3553 (2024) - [i11]Liang Ding, Rui Tuo:
A General Theory for Kernel Packets: from state space model to compactly supported basis. CoRR abs/2402.04022 (2024) - [i10]Haoyuan Chen, Rui Tuo:
Aggregation Models with Optimal Weights for Distributed Gaussian Processes. CoRR abs/2408.00955 (2024) - 2023
- [j15]Abhinav Prakash, Rui Tuo, Yu Ding:
The Temporal Overfitting Problem with Applications in Wind Power Curve Modeling. Technometrics 65(1): 70-82 (2023) - [i9]Rui Tuo, Raktim Bhattacharya:
Privacy-aware Gaussian Process Regression. CoRR abs/2305.16541 (2023) - 2022
- [j14]Haoyuan Chen, Liang Ding, Rui Tuo:
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations. J. Mach. Learn. Res. 23: 127:1-127:32 (2022) - [j13]Abhinav Prakash, Rui Tuo, Yu Ding:
Gaussian Process-Aided Function Comparison Using Noisy Scattered Data. Technometrics 64(1): 92-102 (2022) - [c3]Rui Tuo, Wenjia Wang:
Uncertainty Quantification for Bayesian Optimization. AISTATS 2022: 2862-2884 - [i8]Haoyuan Chen, Liang Ding, Rui Tuo:
Kernel Packet: An Exact and Scalable Algorithm for Gaussian Process Regression with Matérn Correlations. CoRR abs/2203.03116 (2022) - [i7]Gecheng Chen, Yu Zhou, Xudong Zhang, Rui Tuo:
Renewing Iterative Self-labeling Domain Adaptation with Application to the Spine Motion Prediction. CoRR abs/2211.09064 (2022) - 2021
- [j12]Wanrong Zhang, Sara Krehbiel, Rui Tuo, Yajun Mei, Rachel Cummings:
Single and Multiple Change-Point Detection with Differential Privacy. J. Mach. Learn. Res. 22: 29:1-29:36 (2021) - [i6]Liang Ding, Rui Tuo, Xiaowei Zhang:
High-Dimensional Simulation Optimization via Brownian Fields and Sparse Grids. CoRR abs/2107.08595 (2021) - [i5]Liang Ding, Rui Tuo, Shahin Shahrampour:
A Sparse Expansion For Deep Gaussian Processes. CoRR abs/2112.05888 (2021) - 2020
- [j11]Rui Tuo, Wenjia Wang:
Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs. J. Mach. Learn. Res. 21: 187:1-187:38 (2020) - [j10]Rui Tuo, Yan Wang, C. F. Jeff Wu:
On the Improved Rates of Convergence for Matérn-Type Kernel Ridge Regression with Application to Calibration of Computer Models. SIAM/ASA J. Uncertain. Quantification 8(4): 1522-1547 (2020) - [c2]Liang Ding, Rui Tuo, Shahin Shahrampour:
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features. ICML 2020: 2545-2555 - [i4]Liang Ding, Rui Tuo, Shahin Shahrampour:
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features. CoRR abs/2002.04195 (2020) - [i3]Gecheng Chen, Rui Tuo:
Projection Pursuit Gaussian Process Regression. CoRR abs/2004.00667 (2020) - [i2]Liang Ding, Rui Tuo, Shahin Shahrampour:
Overcoming the Curse of Dimensionality in Density Estimation with Mixed Sobolev GANs. CoRR abs/2006.03696 (2020)
2010 – 2019
- 2019
- [j9]Rui Tuo:
Adjustments to Computer Models via Projected Kernel Calibration. SIAM/ASA J. Uncertain. Quantification 7(2): 553-578 (2019) - [j8]V. Roshan Joseph, Dianpeng Wang, Li Gu, Shiji Lyu, Rui Tuo:
Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs. Technometrics 61(3): 297-308 (2019) - 2018
- [j7]Zhiming Chen, Rui Tuo, Wenlong Zhang:
Stochastic Convergence of a Nonconforming Finite Element Method for the Thin Plate Spline Smoother for Observational Data. SIAM J. Numer. Anal. 56(2): 635-659 (2018) - [c1]Rachel Cummings, Sara Krehbiel, Yajun Mei, Rui Tuo, Wanrong Zhang:
Differentially Private Change-Point Detection. NeurIPS 2018: 10848-10857 - [i1]Rachel Cummings, Sara Krehbiel, Yajun Mei, Rui Tuo, Wanrong Zhang:
Differentially Private Change-Point Detection. CoRR abs/1808.10056 (2018) - 2017
- [j6]Xu He, Rui Tuo, C. F. Jeff Wu:
Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion. Technometrics 59(1): 58-68 (2017) - 2016
- [j5]Rui Tuo, C. F. Jeff Wu:
A Theoretical Framework for Calibration in Computer Models: Parametrization, Estimation and Convergence Properties. SIAM/ASA J. Uncertain. Quantification 4(1): 767-795 (2016) - 2015
- [j4]V. Roshan Joseph, Tirthankar Dasgupta, Rui Tuo, C. F. Jeff Wu:
Sequential Exploration of Complex Surfaces Using Minimum Energy Designs. Technometrics 57(1): 64-74 (2015) - 2014
- [j3]Rui Tuo, C. F. Jeff Wu, Dan Yu:
Surrogate Modeling of Computer Experiments With Different Mesh Densities. Technometrics 56(3): 372-380 (2014) - [j2]Matthew Plumlee, Rui Tuo:
Building Accurate Emulators for Stochastic Simulations via Quantile Kriging. Technometrics 56(4): 466-473 (2014) - 2013
- [j1]Rui Tuo, Peter Z. G. Qian, C. F. Jeff Wu:
Comment: A Brownian Motion Model for Stochastic Simulation With Tunable Precision. Technometrics 55(1): 29-31 (2013)
Coauthor Index
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last updated on 2025-09-28 21:59 CEST by the dblp team
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