Yuhao Wang | 王禹皓 - Google Scholar

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Caroline UhlerMassachusetts Institute of TechnologyVerified email at mit.edu
Liam SolusKTH Royal Institute of TechnologyVerified email at kth.se
Santiago SegarraAssistant Professor, Electrical and Computer Engineering, Rice UniversityVerified email at rice.edu
Karren YangMassachusetts Institute of TechnologyVerified email at mit.edu
Anastasiya BelyaevaGoogle ResearchVerified email at google.com
Yaron OrensteinComputer Science and Life Sciences, Bar-Ilan UniversityVerified email at biu.ac.il
Laëtitia CommingesCEREMADE Paris-Dauphine Verified email at dauphine.fr
Xinran LiAssistant professor at University of ChicagoVerified email at uchicago.edu
Nathan KallusCornell UniversityVerified email at cornell.edu
Xiaojie Mao (毛小介)Assistant Professor, School of Economics and Management, Tsinghua UniversityVerified email at sem.tsinghua.edu.cn
guido imbensStanford UniversityVerified email at stanford.edu
Xin HeDepartment of Human Genetics, University of ChicagoVerified email at uchicago.edu
Ziv Bar-JosephProfessor of Computational Biology and Machine Learning, School of Computer Science, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Rajen D. ShahUniversity of CambridgeVerified email at cam.ac.uk
lin liushanghai jiao tong universityVerified email at mail.harvard.edu
Weiming ZhuInnovation and Information Management, The University of Hong KongVerified email at hku.hk
Alexandra CarpentierUni Potsdam

Yuhao Wang | 王禹皓

Institute for Interdisciplinary Information Sciences, Tsinghua University

Verified email at tsinghua.edu.cn - Homepage

causal inference experimental design high-dimensional statistics


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Predicting drug-target interactions using restricted Boltzmann machines Y Wang, J Zeng Bioinformatics 29 (13), i126-i134, 2013	236	2013
Permutation-based causal inference algorithms with interventions Y Wang, L Solus, K Yang, C Uhler Advances in Neural Information Processing Systems 30, 2017	123	2017
Consistency guarantees for greedy permutation-based causal inference algorithms L Solus, Y Wang, C Uhler Biometrika 108 (4), 795-814, 2021	109	2021
RCK: accurate and efficient inference of sequence-and structure-based protein–RNA binding models from RNAcompete data Y Orenstein, Y Wang, B Berger Bioinformatics 32 (12), i351-i359, 2016	78	2016
Permutation-based causal structure learning with unknown intervention targets C Squires, Y Wang, C Uhler Conference on Uncertainty in Artificial Intelligence, 1039-1048, 2020	69	2020
Direct estimation of differences in causal graphs Y Wang, C Squires, A Belyaeva, C Uhler Advances in neural information processing systems 31, 2018	33	2018
Joint inference of multiple graphs from matrix polynomials M Navarro, Y Wang, AG Marques, C Uhler, S Segarra Journal of machine learning research 23 (76), 1-35, 2022	31	2022
Minimax rate of testing in sparse linear regression A Carpentier, O Collier, L Comminges, AB Tsybakov, Y Wang Automation and Remote Control 80, 1817-1834, 2019	28	2019
Learning High-dimensional Gaussian Graphical Models under Total Positivity without Adjustment of Tuning Parameters Y Wang, U Roy, C Uhler International Conference on Artificial Intelligence and Statistics, 2698-2708, 2020	26	2020
High-dimensional joint estimation of multiple directed Gaussian graphical models Y Wang, S Segarra, C Uhler Electronic Journal of Statistics 14 (1), 2439-2483, 2020	26	2020
Joint inference of networks from stationary graph signals S Segarra, Y Wang, C Uhler, AG Marques 2017 51st Asilomar Conference on Signals, Systems, and Computers, 975-979, 2017	25	2017
Long-term Causal Inference Under Persistent Confounding via Data Combination G Imbens, N Kallus, X Mao, Y Wang arXiv preprint arXiv:2202.07234, 2022	23	2022
De novo ChIP-seq analysis X He, AE Cicek, Y Wang, MH Schulz, HS Le, Z Bar-Joseph Genome biology 16, 1-10, 2015	16	2015
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders Y Wang, RD Shah arXiv preprint arXiv:2011.08661, 2020	15	2020
Rerandomization with diminishing covariate imbalance and diverging number of covariates Y Wang, X Li The Annals of Statistics 50 (6), 3439-3465, 2022	12	2022
Anchored Causal Inference in the Presence of Measurement Error B Saeed, A Belyaeva, Y Wang, C Uhler Conference on Uncertainty in Artificial Intelligence, 619-628, 2020	8	2020
Estimation of the ℓ2-norm and testing in sparse linear regression with unknown variance A Carpentier, O Collier, L Comminges, AB Tsybakov, Y Wang Bernoulli 28 (4), 2744-2787, 2022	6	2022
Residual Permutation Test for High-Dimensional Regression Coefficient Testing K Wen, T Wang, Y Wang arXiv preprint arXiv:2211.16182, 2022	3	2022
Debiased Regression Adjustment in Completely Randomized Experiments with Moderately High-dimensional Covariates X Lu, F Yang, Y Wang arXiv preprint arXiv:2309.02073, 2023	2	2023
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity L Liu, Y Wang arXiv preprint arXiv:2305.04174, 2023	1	2023

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