A numerical method for the study of nucleation of ordered phases. - Ling Lin; Xiuyuan Cheng; Weinan E; An-Chang Shi; Pingwen Zhang (J. Comput. Phys., 2010)

Expected performance bounds for estimation on graphs from random relative measurements. - Nicolas Boumal; Xiuyuan Cheng (CoRR, 2013)

Unsupervised Deep Haar Scattering on Graphs. - Xu Chen; Xiuyuan Cheng; Stéphane Mallat (NIPS, 2014)

Unsupervised Learning by Deep Scattering Contractions. - Xu Chen; Xiuyuan Cheng; Stéphane Mallat (CoRR, 2014)

Concentration of the Kirchhoff index for Erdős-Rényi graphs. - Nicolas Boumal; Xiuyuan Cheng (Syst. Control. Lett., 2014)

Deep Haar Scattering Networks. - Xiuyuan Cheng; Xu Chen; Stéphane Mallat (CoRR, 2015)

Rotating MaxRS queries. - Zitong Chen; Yubao Liu; Raymond Chi-Wing Wong; Jiamin Xiong; Xiuyuan Cheng; Peihuan Chen (Inf. Sci., 2015)

A Deep Learning Approach to Unsupervised Ensemble Learning. - Uri Shaham 001; Xiuyuan Cheng; Omer Dror; Ariel Jaffe; Boaz Nadler; Joseph T. Chang; Yuval Kluger (ICML, 2016)

Marčenko-Pastur law for Tyler's M-estimator. - Teng Zhang 002; Xiuyuan Cheng; Amit Singer (J. Multivar. Anal., 2016)

A Graph Partitioning Approach to Simultaneous Angular Reconstitution. - Gabi Pragier; Ido Greenberg; Xiuyuan Cheng; Yoel Shkolnisky (IEEE Trans. Computational Imaging, 2016)

Two-sample Statistics Based on Anisotropic Kernels. - Xiuyuan Cheng; Alexander Cloninger; Ronald R. Coifman (CoRR, 2017)

Provable Estimation of the Number of Blocks in Block Models. - Bowei Yan; Purnamrita Sarkar; Xiuyuan Cheng (AISTATS, 2018)

DCFNet: Deep Neural Network with Decomposed Convolutional Filters. - Qiang Qiu 001; Xiuyuan Cheng; A. Robert Calderbank; Guillermo Sapiro (ICML, 2018)

Defending against Adversarial Images using Basis Functions Transformations. - Uri Shaham 001; James Garritano; Yutaro Yamada; Ethan Weinberger; Alex Cloninger; Xiuyuan Cheng; Kelly P. Stanton; Yuval Kluger (CoRR, 2018)

Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks. - Yingzhou Li; Xiuyuan Cheng; Jianfeng Lu 001 (CoRR, 2018)

RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks. - Xiuyuan Cheng; Qiang Qiu 001; A. Robert Calderbank; Guillermo Sapiro (ICLR (Poster), 2019)

Diffusion Variational Autoencoders. - Henry Li; Ofir Lindenbaum; Xiuyuan Cheng; Alexander Cloninger (CoRR, 2019)

Scale-Equivariant Neural Networks with Decomposed Convolutional Filters. - Wei Zhu 007; Qiang Qiu 001; A. Robert Calderbank; Guillermo Sapiro; Xiuyuan Cheng (CoRR, 2019)

Domain-invariant Learning using Adaptive Filter Decomposition. - Ze Wang 008; Xiuyuan Cheng; Guillermo Sapiro; Qiang Qiu 001 (CoRR, 2019)

Classification Logit Two-sample Testing by Neural Networks. - Xiuyuan Cheng; Alexander Cloninger (CoRR, 2019)

Variational Diffusion Autoencoders with Random Walk Sampling. - Henry Li; Ofir Lindenbaum; Xiuyuan Cheng; Alexander Cloninger (ECCV (23), 2020)

Stochastic Conditional Generative Networks with Basis Decomposition. - Ze Wang 008; Xiuyuan Cheng; Guillermo Sapiro; Qiang Qiu 001 (ICLR, 2020)

Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization. - Zhongshu Xu; Yingzhou Li; Xiuyuan Cheng (MSML, 2020)

A Dictionary Approach to Domain-Invariant Learning in Deep Networks. - Ze Wang 008; Xiuyuan Cheng; Guillermo Sapiro; Qiang Qiu 001 (NeurIPS, 2020)

Graph Neural Networks with Low-rank Learnable Local Filters. - Xiuyuan Cheng; Zichen Miao; Qiang Qiu (CoRR, 2020)

ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution. - Ze Wang 008; Xiuyuan Cheng; Guillermo Sapiro; Qiang Qiu 001 (CoRR, 2020)

Convergence of Graph Laplacian with kNN Self-tuned Kernels. - Xiuyuan Cheng; Hau-Tieng Wu (CoRR, 2020)

A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials. - Hrushikesh N. Mhaskar; Xiuyuan Cheng; Alexander Cloninger (Frontiers Appl. Math. Stat., 2020)

Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. - Xiuyuan Cheng; Gal Mishne (SIAM J. Imaging Sci., 2020)

Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples. - Yixing Zhang; Xiuyuan Cheng; Galen Reeves (AISTATS, 2021)

Graph Convolution with Low-rank Learnable Local Filters. - Xiuyuan Cheng; Zichen Miao; Qiang Qiu (ICLR, 2021)

Neural Tangent Kernel Maximum Mean Discrepancy. - Xiuyuan Cheng; Yao Xie 002 (NeurIPS, 2021)

Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks. - Zichen Miao; Ze Wang 008; Xiuyuan Cheng; Qiang Qiu 001 (NeurIPS, 2021)

Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation. - Xiuyuan Cheng; Nan Wu (CoRR, 2021)

Kernel MMD Two-Sample Tests for Manifold Data. - Xiuyuan Cheng; Yao Xie 002 (CoRR, 2021)

Neural Spectral Marked Point Processes. - Shixiang Zhu; Haoyun Wang; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2021)

Neural Spectral Marked Point Processes. - Shixiang Zhu; Haoyun Wang; Zheng Dong 005; Xiuyuan Cheng; Yao Xie 002 (ICLR, 2022)

SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks. - Ziyu Chen; Yingzhou Li; Xiuyuan Cheng (MSML, 2022)

Police Text Analysis: Topic Modeling and Spatial Relative Density Estimation. - Sarah Huestis-Mitchell; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2022)

Training neural networks using monotone variational inequality. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2022)

Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise. - Xiuyuan Cheng; Boris Landa (CoRR, 2022)

Invertible normalizing flow neural networks by JKO scheme. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2022)

Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters. - Wei Zhu 007; Qiang Qiu 001; A. Robert Calderbank; Guillermo Sapiro; Xiuyuan Cheng (J. Mach. Learn. Res., 2022)

Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities. - Xiuyuan Cheng; Alexander Cloninger (IEEE Trans. Inf. Theory, 2022)

Invertible Neural Networks for Graph Prediction. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (IEEE J. Sel. Areas Inf. Theory, 2022)

Training Neural Networks for Sequential Change-Point Detection. - Junghwan Lee; Yao Xie 002; Xiuyuan Cheng (ICASSP, 2023)

Spatio-temporal point processes with deep non-stationary kernels. - Zheng Dong 005; Xiuyuan Cheng; Yao Xie 002 (ICLR, 2023)

Normalizing flow neural networks by JKO scheme. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (NeurIPS, 2023)

The G-invariant graph Laplacian. - Eitan Rosen; Xiuyuan Cheng; Yoel Shkolnisky (CoRR, 2023)

Optimal transport flow and infinitesimal density ratio estimation. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2023)

Neural Differential Recurrent Neural Network with Adaptive Time Steps. - Yixuan Tan; Liyan Xie; Xiuyuan Cheng (CoRR, 2023)

G-invariant diffusion maps. - Eitan Rosen; Xiuyuan Cheng; Yoel Shkolnisky (CoRR, 2023)

Deep graph kernel point processes. - Zheng Dong 005; Matthew Repasky; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2023)

Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. - Boris Landa; Xiuyuan Cheng (SIAM J. Math. Data Sci., 2023)

Neural Stein Critics With Staged L 2-Regularization. - Matthew Repasky; Xiuyuan Cheng; Yao Xie 002 (IEEE Trans. Inf. Theory, 2023)

Stage-Regularized Neural Stein Critics For Testing Goodness-Of-Fit Of Generative Models. - Matthew Repasky; Xiuyuan Cheng; Yao Xie 002 (ICASSP, 2024)

Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis. - Varun Khurana; Xiuyuan Cheng; Alexander Cloninger (CoRR, 2024)

Posterior sampling via Langevin dynamics based on generative priors. - Vishal Purohit; Matthew Repasky; Jianfeng Lu 001; Qiang Qiu 001; Yao Xie 002; Xiuyuan Cheng (CoRR, 2024)

Local Flow Matching Generative Models. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (CoRR, 2024)

Improved convergence rate of kNN graph Laplacians. - Yixuan Tan; Xiuyuan Cheng (CoRR, 2024)

Point processes with event time uncertainty. - Xiuyuan Cheng; Tingnan Gong; Yao Xie 002 (CoRR, 2024)

Flow-Based Distributionally Robust Optimization. - Chen Xu; Jonghyeok Lee; Xiuyuan Cheng; Yao Xie 002 (IEEE J. Sel. Areas Inf. Theory, 2024)

Convergence of Flow-Based Generative Models via Proximal Gradient Descent in Wasserstein Space. - Xiuyuan Cheng; Jianfeng Lu 001; Yixin Tan; Yao Xie 002 (IEEE Trans. Inf. Theory, 2024)

Computing high-dimensional optimal transport by flow neural networks. - Chen Xu; Xiuyuan Cheng; Yao Xie 002 (AISTATS, 2025)

Consistency Posterior Sampling for Diverse Image Synthesis. - Vishal Purohit; Matthew Repasky; Jianfeng Lu 001; Qiang Qiu 001; Yao Xie 002; Xiuyuan Cheng (CVPR, 2025)

Flow-based generative models as iterative algorithms in probability space. - Yao Xie 002; Xiuyuan Cheng (CoRR, 2025)

Deep spatio-temporal point processes: Advances and new directions. - Xiuyuan Cheng; Zheng Dong 005; Yao Xie 002 (CoRR, 2025)