Xiuyuan Cheng

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 68

Top Topics

Top Venues

IEEE Trans. Inf. Theory

Publications

Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, Yao Xie
Flow-Based Distributionally Robust Optimization. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Varun Khurana, Xiuyuan Cheng, Alexander Cloninger
Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis. CoRR (2024)
Matthew Repasky, Xiuyuan Cheng, Yao Xie
Stage-Regularized Neural Stein Critics For Testing Goodness-Of-Fit Of Generative Models. ICASSP (2024)
Chen Xu, Xiuyuan Cheng, Yao Xie
Q-malizing flow and infinitesimal density ratio estimation. CoRR (2023)
Matthew Repasky, Xiuyuan Cheng, Yao Xie
-Regularization. IEEE Trans. Inf. Theory 69 (11) (2023)
Zheng Dong, Xiuyuan Cheng, Yao Xie
Spatio-temporal point processes with deep non-stationary kernels. ICLR (2023)
Boris Landa, Xiuyuan Cheng
Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. SIAM J. Math. Data Sci. 5 (3) (2023)
Chen Xu, Xiuyuan Cheng, Yao Xie
Normalizing flow neural networks by JKO scheme. NeurIPS (2023)
Junghwan Lee, Yao Xie, Xiuyuan Cheng
Training Neural Networks for Sequential Change-Point Detection. ICASSP (2023)
Yixuan Tan, Liyan Xie, Xiuyuan Cheng
Neural Differential Recurrent Neural Network with Adaptive Time Steps. CoRR (2023)
Eitan Rosen, Xiuyuan Cheng, Yoel Shkolnisky
G-invariant diffusion maps. CoRR (2023)
Xiuyuan Cheng, Jianfeng Lu, Yixin Tan, Yao Xie
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space. CoRR (2023)
Eitan Rosen, Xiuyuan Cheng, Yoel Shkolnisky
The G-invariant graph Laplacian. CoRR (2023)
Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, Yao Xie
Flow-based Distributionally Robust Optimization. CoRR (2023)
Zheng Dong, Matthew Repasky, Xiuyuan Cheng, Yao Xie
Deep graph kernel point processes. CoRR (2023)
Matthew Repasky, Xiuyuan Cheng, Yao Xie
-regularization. CoRR (2022)
Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie
Neural Spectral Marked Point Processes. ICLR (2022)
Boris Landa, Xiuyuan Cheng
Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. CoRR (2022)
Chen Xu, Xiuyuan Cheng, Yao Xie
Invertible Neural Networks for Graph Prediction. IEEE J. Sel. Areas Inf. Theory 3 (3) (2022)
Xiuyuan Cheng, Alexander Cloninger
Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities. IEEE Trans. Inf. Theory 68 (10) (2022)
Junghwan Lee, Yao Xie, Xiuyuan Cheng
Training Neural Networks for Sequential Change-point Detection. CoRR (2022)
Chen Xu, Xiuyuan Cheng, Yao Xie
Training neural networks using monotone variational inequality. CoRR (2022)
Xiuyuan Cheng, Boris Landa
Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise. CoRR (2022)
Wei Zhu, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng
Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters. J. Mach. Learn. Res. 23 (2022)
Ziyu Chen, Yingzhou Li, Xiuyuan Cheng
SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks. MSML (2022)
Chen Xu, Xiuyuan Cheng, Yao Xie
Invertible Neural Networks for Graph Prediction. CoRR (2022)
Ziyu Chen, Yingzhou Li, Xiuyuan Cheng
SpecNet2: Orthogonalization-free spectral embedding by neural networks. CoRR (2022)
Zheng Dong, Xiuyuan Cheng, Yao Xie
Spatio-temporal point processes with deep non-stationary kernels. CoRR (2022)
Sarah Huestis-Mitchell, Xiuyuan Cheng, Yao Xie
Police Text Analysis: Topic Modeling and Spatial Relative Density Estimation. CoRR (2022)
Chen Xu, Xiuyuan Cheng, Yao Xie
Invertible normalizing flow neural networks by JKO scheme. CoRR (2022)
Xiuyuan Cheng, Yao Xie
Kernel MMD Two-Sample Tests for Manifold Data. CoRR (2021)
Zichen Miao, Ze Wang, Xiuyuan Cheng, Qiang Qiu
Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks. NeurIPS (2021)
Xiuyuan Cheng, Nan Wu
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation. CoRR (2021)
Xiuyuan Cheng, Yao Xie
Neural Tangent Kernel Maximum Mean Discrepancy. NeurIPS (2021)
Yixing Zhang, Xiuyuan Cheng, Galen Reeves
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples. CoRR (2021)
Yixing Zhang, Xiuyuan Cheng, Galen Reeves
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples. AISTATS (2021)
Xiuyuan Cheng, Yao Xie
Neural Tangent Kernel Maximum Mean Discrepancy. CoRR (2021)
Shixiang Zhu, Haoyun Wang, Xiuyuan Cheng, Yao Xie
Neural Spectral Marked Point Processes. CoRR (2021)
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Graph Convolution with Low-rank Learnable Local Filters. ICLR (2021)
Xiuyuan Cheng, Zichen Miao, Qiang Qiu
Graph Neural Networks with Low-rank Learnable Local Filters. CoRR (2020)
Hrushikesh N. Mhaskar, Xiuyuan Cheng, Alexander Cloninger
A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials. Frontiers Appl. Math. Stat. 6 (2020)
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
Variational Diffusion Autoencoders with Random Walk Sampling. ECCV (23) (2020)
Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution. CoRR (2020)
Xiuyuan Cheng, Hau-Tieng Wu
Convergence of Graph Laplacian with kNN Self-tuned Kernels. CoRR (2020)
Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
Stochastic Conditional Generative Networks with Basis Decomposition. ICLR (2020)
Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
A Dictionary Approach to Domain-Invariant Learning in Deep Networks. NeurIPS (2020)
Zhongshu Xu, Yingzhou Li, Xiuyuan Cheng
Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization. MSML (2020)
Xiuyuan Cheng, Gal Mishne
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. SIAM J. Imaging Sci. 13 (2) (2020)
Hrushikesh N. Mhaskar, Alex Cloninger, Xiuyuan Cheng
A witness function based construction of discriminative models using Hermite polynomials. CoRR (2019)
Xiuyuan Cheng, Alexander Cloninger
Classification Logit Two-sample Testing by Neural Networks. CoRR (2019)
Zhongshu Xu, Yingzhou Li, Xiuyuan Cheng
Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization. CoRR (2019)
Xiuyuan Cheng, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks. ICLR (Poster) (2019)
Wei Zhu, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng
Scale-Equivariant Neural Networks with Decomposed Convolutional Filters. CoRR (2019)
Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
Domain-invariant Learning using Adaptive Filter Decomposition. CoRR (2019)
Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
Stochastic Conditional Generative Networks with Basis Decomposition. CoRR (2019)
Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
Diffusion Variational Autoencoders. CoRR (2019)
Qiang Qiu, Xiuyuan Cheng, A. Robert Calderbank, Guillermo Sapiro
DCFNet: Deep Neural Network with Decomposed Convolutional Filters. ICML (2018)
Xiuyuan Cheng, Gal Mishne
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. CoRR (2018)
Qiang Qiu, Xiuyuan Cheng, A. Robert Calderbank, Guillermo Sapiro
DCFNet: Deep Neural Network with Decomposed Convolutional Filters. CoRR (2018)
Uri Shaham, James Garritano, Yutaro Yamada, Ethan Weinberger, Alex Cloninger, Xiuyuan Cheng, Kelly P. Stanton, Yuval Kluger
Defending against Adversarial Images using Basis Functions Transformations. CoRR (2018)
Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng
Provable Estimation of the Number of Blocks in Block Models. AISTATS (2018)
Yingzhou Li, Xiuyuan Cheng, Jianfeng Lu
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks. CoRR (2018)
Xiuyuan Cheng, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro
RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks. CoRR (2018)
Xiuyuan Cheng, Alexander Cloninger, Ronald R. Coifman
Two-sample Statistics Based on Anisotropic Kernels. CoRR (2017)
Teng Zhang, Xiuyuan Cheng, Amit Singer
Marčenko-Pastur law for Tyler's M-estimator. J. Multivar. Anal. 149 (2016)
Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
A Deep Learning Approach to Unsupervised Ensemble Learning. CoRR (2016)
Gabi Pragier, Ido Greenberg, Xiuyuan Cheng, Yoel Shkolnisky
A Graph Partitioning Approach to Simultaneous Angular Reconstitution. IEEE Trans. Computational Imaging 2 (3) (2016)
Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
A Deep Learning Approach to Unsupervised Ensemble Learning. ICML (2016)
Zitong Chen, Yubao Liu, Raymond Chi-Wing Wong, Jiamin Xiong, Xiuyuan Cheng, Peihuan Chen
Rotating MaxRS queries. Inf. Sci. 305 (2015)
Xiuyuan Cheng, Xu Chen, Stéphane Mallat
Deep Haar Scattering Networks. CoRR (2015)
Xu Chen, Xiuyuan Cheng, Stéphane Mallat
Unsupervised Deep Haar Scattering on Graphs. NIPS (2014)
Nicolas Boumal, Xiuyuan Cheng
Concentration of the Kirchhoff index for Erdős-Rényi graphs. Syst. Control. Lett. 74 (2014)
Xu Chen, Xiuyuan Cheng, Stéphane Mallat
Unsupervised Learning by Deep Scattering Contractions. CoRR (2014)
Nicolas Boumal, Xiuyuan Cheng
Expected performance bounds for estimation on graphs from random relative measurements. CoRR (2013)
Ling Lin, Xiuyuan Cheng, Weinan E, An-Chang Shi, Pingwen Zhang
A numerical method for the study of nucleation of ordered phases. J. Comput. Phys. 229 (5) (2010)