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Xiuyuan Cheng
Xiuyuan Cheng
Verified email at duke.edu - Homepage
Title
Cited by
Cited by
Year
Prevalence, awareness, treatment, and control of hypertension in China: data from 1· 7 million adults in a population-based screening study (China PEACE Million Persons Project)
J Lu, Y Lu, X Wang, X Li, GC Linderman, C Wu, X Cheng, L Mu, H Zhang, ...
The Lancet 390 (10112), 2549-2558, 2017
10632017
Nucleation of ordered phases in block copolymers
X Cheng, L Lin, W E, P Zhang, AC Shi
Physical review letters 104 (14), 148301, 2010
134*2010
The spectrum of random inner-product kernel matrices
X Cheng, A Singer
Random Matrices: Theory and Applications 2 (04), 1350010, 2013
1092013
Detection of differentially abundant cell subpopulations in scRNA-seq data
J Zhao, A Jaffe, H Li, O Lindenbaum, E Sefik, R Jackson, X Cheng, ...
Proceedings of the National Academy of Sciences 118 (22), e2100293118, 2021
1072021
DCFNet: Deep neural network with decomposed convolutional filters
Q Qiu, X Cheng, R Calderbank, G Sapiro
International Conference on Machine Learning, 4198-4207, 2018
762018
Defending against adversarial images using basis functions transformations
U Shaham, J Garritano, Y Yamada, E Weinberger, A Cloninger, X Cheng, ...
arXiv preprint arXiv:1803.10840, 2018
752018
Unsupervised deep haar scattering on graphs
X Chen, X Cheng, S Mallat
Advances in Neural Information Processing Systems 27, 2014
652014
Marčenko–Pastur law for Tyler’s M-estimator
T Zhang, X Cheng, A Singer
Journal of Multivariate Analysis 149, 114-123, 2016
562016
Rotdcf: Decomposition of convolutional filters for rotation-equivariant deep networks
X Cheng, Q Qiu, R Calderbank, G Sapiro
arXiv preprint arXiv:1805.06846, 2018
462018
A deep learning approach to unsupervised ensemble learning
U Shaham, X Cheng, O Dror, A Jaffe, B Nadler, J Chang, Y Kluger
International conference on machine learning, 30-39, 2016
452016
Scale-equivariant neural networks with decomposed convolutional filters
W Zhu, Q Qiu, R Calderbank, G Sapiro, X Cheng
43*2019
Classification logit two-sample testing by neural networks for differentiating near manifold densities
X Cheng, A Cloninger
IEEE transactions on information theory 68 (10), 6631-6662, 2022
422022
Provable estimation of the number of blocks in block models
B Yan, P Sarkar, X Cheng
Proceedings of the Twenty-First International Conference on Artificial …, 2018
42*2018
Deep Haar scattering networks
X Cheng, X Chen, S Mallat
Information and Inference: A Journal of the IMA 5 (2), 105-133, 2016
422016
Neural tangent kernel maximum mean discrepancy
X Cheng, Y Xie
Advances in Neural Information Processing Systems 34, 6658-6670, 2021
272021
A numerical method for the study of nucleation of ordered phases
L Lin, X Cheng, E Weinan, AC Shi, P Zhang
Journal of Computational Physics 229 (5), 1797-1809, 2010
252010
On the diffusion geometry of graph Laplacians and applications
X Cheng, M Rachh, S Steinerberger
Applied and Computational Harmonic Analysis 46 (3), 674-688, 2019
232019
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
X Cheng, N Wu
Applied and Computational Harmonic Analysis 61, 132-190, 2022
222022
Two-sample statistics based on anisotropic kernels
X Cheng, A Cloninger, RR Coifman
Information and Inference: A Journal of the IMA 9 (3), 677-719, 2020
212020
Butterfly-Net: Optimal function representation based on convolutional neural networks
Y Li, X Cheng, J Lu
arXiv preprint arXiv:1805.07451, 2018
212018
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Articles 1–20