Xiuyuan Cheng - RankMe

88 papers A* 11A 3Misc 2Journal 67Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Flow-Based Generative Models as Iterative Algorithms in Probability Space: An intuitive mathematical framework [Special Issue on the Mathematics of Deep Learning]. IEEE Signal Process. Mag. Yao Xie, Xiuyuan Cheng
2026	J	`jnl`	Local Flow Matching Generative Models. IEEE Trans. Inf. Theory Chen Xu, Xiuyuan Cheng, Yao Xie
2025	A	`conf`	Computing high-dimensional optimal transport by flow neural networks. AISTATS Chen Xu, Xiuyuan Cheng, Yao Xie
2025	A*	`conf`	Consistency Posterior Sampling for Diverse Image Synthesis. CVPR Vishal Purohit, Matthew Repasky, Jianfeng Lu, Qiang Qiu, Yao Xie, Xiuyuan Cheng
2025	J	`jnl`	Deep spatio-temporal point processes: Advances and new directions. CoRR Xiuyuan Cheng, Zheng Dong, Yao Xie
2025	J	`jnl`	Flow-based generative models as iterative algorithms in probability space. CoRR Yao Xie, Xiuyuan Cheng
2025	J	`jnl`	High-dimensional Mean-Field Games by Particle-based Flow Matching. CoRR Jiajia Yu, Junghwan Lee, Yao Xie, Xiuyuan Cheng
2025	J	`jnl`	Worst-case generation via minimax optimization in Wasserstein space. CoRR Xiuyuan Cheng, Yao Xie, Linglingzhi Zhu, Yunqin Zhu
2024	J	`jnl`	Convergence of Flow-Based Generative Models via Proximal Gradient Descent in Wasserstein Space. IEEE Trans. Inf. Theory Xiuyuan Cheng, Jianfeng Lu, Yixin Tan, Yao Xie
2024	J	`jnl`	Flow-Based Distributionally Robust Optimization. IEEE J. Sel. Areas Inf. Theory Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, Yao Xie
2024	J	`jnl`	Improved convergence rate of kNN graph Laplacians. CoRR Yixuan Tan, Xiuyuan Cheng
2024	J	`jnl`	Local Flow Matching Generative Models. CoRR Chen Xu, Xiuyuan Cheng, Yao Xie
2024	J	`jnl`	Point processes with event time uncertainty. CoRR Xiuyuan Cheng, Tingnan Gong, Yao Xie
2024	J	`jnl`	Posterior sampling via Langevin dynamics based on generative priors. CoRR Vishal Purohit, Matthew Repasky, Jianfeng Lu, Qiang Qiu, Yao Xie, Xiuyuan Cheng
2024	Misc	`conf`	Stage-Regularized Neural Stein Critics For Testing Goodness-Of-Fit Of Generative Models. ICASSP Matthew Repasky, Xiuyuan Cheng, Yao Xie
2024	J	`jnl`	Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis. CoRR Varun Khurana, Xiuyuan Cheng, Alexander Cloninger
2023	J	`jnl`	Convergence of flow-based generative models via proximal gradient descent in Wasserstein space. CoRR Xiuyuan Cheng, Jianfeng Lu, Yixin Tan, Yao Xie
2023	J	`jnl`	Deep graph kernel point processes. CoRR Zheng Dong, Matthew Repasky, Xiuyuan Cheng, Yao Xie
2023	J	`jnl`	Flow-based Distributionally Robust Optimization. CoRR Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, Yao Xie
2023	J	`jnl`	G-invariant diffusion maps. CoRR Eitan Rosen, Xiuyuan Cheng, Yoel Shkolnisky
2023	J	`jnl`	Neural Differential Recurrent Neural Network with Adaptive Time Steps. CoRR Yixuan Tan, Liyan Xie, Xiuyuan Cheng
2023	J	`jnl`	Neural Stein Critics With Staged L IEEE Trans. Inf. Theory Matthew Repasky, Xiuyuan Cheng, Yao Xie
2023	A*	`conf`	Normalizing flow neural networks by JKO scheme. NeurIPS Chen Xu, Xiuyuan Cheng, Yao Xie
2023	J	`jnl`	Optimal transport flow and infinitesimal density ratio estimation. CoRR Chen Xu, Xiuyuan Cheng, Yao Xie
2023	J	`jnl`	Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. SIAM J. Math. Data Sci. Boris Landa, Xiuyuan Cheng
2023	A*	`conf`	Spatio-temporal point processes with deep non-stationary kernels. ICLR Zheng Dong, Xiuyuan Cheng, Yao Xie
2023	J	`jnl`	The G-invariant graph Laplacian. CoRR Eitan Rosen, Xiuyuan Cheng, Yoel Shkolnisky
2023	Misc	`conf`	Training Neural Networks for Sequential Change-Point Detection. ICASSP Junghwan Lee, Yao Xie, Xiuyuan Cheng
2022	J	`jnl`	Bi-stochastically normalized graph Laplacian: convergence to manifold Laplacian and robustness to outlier noise. CoRR Xiuyuan Cheng, Boris Landa
2022	J	`jnl`	Classification Logit Two-Sample Testing by Neural Networks for Differentiating Near Manifold Densities. IEEE Trans. Inf. Theory Xiuyuan Cheng, Alexander Cloninger
2022	J	`jnl`	Invertible Neural Networks for Graph Prediction. CoRR Chen Xu, Xiuyuan Cheng, Yao Xie
2022	J	`jnl`	Invertible Neural Networks for Graph Prediction. IEEE J. Sel. Areas Inf. Theory Chen Xu, Xiuyuan Cheng, Yao Xie
2022	J	`jnl`	Invertible normalizing flow neural networks by JKO scheme. CoRR Chen Xu, Xiuyuan Cheng, Yao Xie
2022	A*	`conf`	Neural Spectral Marked Point Processes. ICLR Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie
2022	J	`jnl`	Neural Stein critics with staged L CoRR Matthew Repasky, Xiuyuan Cheng, Yao Xie
2022	J	`jnl`	Police Text Analysis: Topic Modeling and Spatial Relative Density Estimation. CoRR Sarah Huestis-Mitchell, Xiuyuan Cheng, Yao Xie
2022	J	`jnl`	Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling. CoRR Boris Landa, Xiuyuan Cheng
2022	J	`jnl`	Scaling-Translation-Equivariant Networks with Decomposed Convolutional Filters. J. Mach. Learn. Res. Wei Zhu, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng
2022	J	`jnl`	Spatio-temporal point processes with deep non-stationary kernels. CoRR Zheng Dong, Xiuyuan Cheng, Yao Xie
2022	—	`conf`	SpecNet2: Orthogonalization-free Spectral Embedding by Neural Networks. MSML Ziyu Chen, Yingzhou Li, Xiuyuan Cheng
2022	J	`jnl`	SpecNet2: Orthogonalization-free spectral embedding by neural networks. CoRR Ziyu Chen, Yingzhou Li, Xiuyuan Cheng
2022	J	`jnl`	Training Neural Networks for Sequential Change-point Detection. CoRR Junghwan Lee, Yao Xie, Xiuyuan Cheng
2022	J	`jnl`	Training neural networks using monotone variational inequality. CoRR Chen Xu, Xiuyuan Cheng, Yao Xie
2021	A	`conf`	Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples. AISTATS Yixing Zhang, Xiuyuan Cheng, Galen Reeves
2021	J	`jnl`	Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples. CoRR Yixing Zhang, Xiuyuan Cheng, Galen Reeves
2021	J	`jnl`	Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation. CoRR Xiuyuan Cheng, Nan Wu
2021	A*	`conf`	Graph Convolution with Low-rank Learnable Local Filters. ICLR Xiuyuan Cheng, Zichen Miao, Qiang Qiu
2021	J	`jnl`	Kernel MMD Two-Sample Tests for Manifold Data. CoRR Xiuyuan Cheng, Yao Xie
2021	J	`jnl`	Neural Spectral Marked Point Processes. CoRR Shixiang Zhu, Haoyun Wang, Xiuyuan Cheng, Yao Xie
2021	A*	`conf`	Neural Tangent Kernel Maximum Mean Discrepancy. NeurIPS Xiuyuan Cheng, Yao Xie
2021	J	`jnl`	Neural Tangent Kernel Maximum Mean Discrepancy. CoRR Xiuyuan Cheng, Yao Xie
2021	A*	`conf`	Spatiotemporal Joint Filter Decomposition in 3D Convolutional Neural Networks. NeurIPS Zichen Miao, Ze Wang, Xiuyuan Cheng, Qiang Qiu
2020	A*	`conf`	A Dictionary Approach to Domain-Invariant Learning in Deep Networks. NeurIPS Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
2020	J	`jnl`	A Witness Function Based Construction of Discriminative Models Using Hermite Polynomials. Frontiers Appl. Math. Stat. Hrushikesh N. Mhaskar, Xiuyuan Cheng, Alexander Cloninger
2020	J	`jnl`	ACDC: Weight Sharing in Atom-Coefficient Decomposed Convolution. CoRR Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
2020	—	`conf`	Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization. MSML Zhongshu Xu, Yingzhou Li, Xiuyuan Cheng
2020	J	`jnl`	Convergence of Graph Laplacian with kNN Self-tuned Kernels. CoRR Xiuyuan Cheng, Hau-Tieng Wu
2020	J	`jnl`	Graph Neural Networks with Low-rank Learnable Local Filters. CoRR Xiuyuan Cheng, Zichen Miao, Qiang Qiu
2020	J	`jnl`	Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. SIAM J. Imaging Sci. Xiuyuan Cheng, Gal Mishne
2020	A*	`conf`	Stochastic Conditional Generative Networks with Basis Decomposition. ICLR Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
2020	—	`conf`	Variational Diffusion Autoencoders with Random Walk Sampling. ECCV (23) Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
2019	J	`jnl`	A witness function based construction of discriminative models using Hermite polynomials. CoRR Hrushikesh N. Mhaskar, Alex Cloninger, Xiuyuan Cheng
2019	J	`jnl`	Butterfly-Net2: Simplified Butterfly-Net and Fourier Transform Initialization. CoRR Zhongshu Xu, Yingzhou Li, Xiuyuan Cheng
2019	J	`jnl`	Classification Logit Two-sample Testing by Neural Networks. CoRR Xiuyuan Cheng, Alexander Cloninger
2019	J	`jnl`	Diffusion Variational Autoencoders. CoRR Henry Li, Ofir Lindenbaum, Xiuyuan Cheng, Alexander Cloninger
2019	J	`jnl`	Domain-invariant Learning using Adaptive Filter Decomposition. CoRR Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
2019	—	`conf`	RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks. ICLR (Poster) Xiuyuan Cheng, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro
2019	J	`jnl`	Scale-Equivariant Neural Networks with Decomposed Convolutional Filters. CoRR Wei Zhu, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng
2019	J	`jnl`	Stochastic Conditional Generative Networks with Basis Decomposition. CoRR Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
2018	J	`jnl`	Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks. CoRR Yingzhou Li, Xiuyuan Cheng, Jianfeng Lu
2018	A*	`conf`	DCFNet: Deep Neural Network with Decomposed Convolutional Filters. ICML Qiang Qiu, Xiuyuan Cheng, A. Robert Calderbank, Guillermo Sapiro
2018	J	`jnl`	DCFNet: Deep Neural Network with Decomposed Convolutional Filters. CoRR Qiang Qiu, Xiuyuan Cheng, A. Robert Calderbank, Guillermo Sapiro
2018	J	`jnl`	Defending against Adversarial Images using Basis Functions Transformations. CoRR Uri Shaham, James Garritano, Yutaro Yamada, Ethan Weinberger, Alex Cloninger, Xiuyuan Cheng, Kelly P. Stanton, Yuval Kluger
2018	A	`conf`	Provable Estimation of the Number of Blocks in Block Models. AISTATS Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng
2018	J	`jnl`	RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks. CoRR Xiuyuan Cheng, Qiang Qiu, A. Robert Calderbank, Guillermo Sapiro
2018	J	`jnl`	Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian. CoRR Xiuyuan Cheng, Gal Mishne
2017	J	`jnl`	Two-sample Statistics Based on Anisotropic Kernels. CoRR Xiuyuan Cheng, Alexander Cloninger, Ronald R. Coifman
2016	A*	`conf`	A Deep Learning Approach to Unsupervised Ensemble Learning. ICML Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2016	J	`jnl`	A Deep Learning Approach to Unsupervised Ensemble Learning. CoRR Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph T. Chang, Yuval Kluger
2016	J	`jnl`	A Graph Partitioning Approach to Simultaneous Angular Reconstitution. IEEE Trans. Computational Imaging Gabi Pragier, Ido Greenberg, Xiuyuan Cheng, Yoel Shkolnisky
2016	J	`jnl`	Marčenko-Pastur law for Tyler's M-estimator. J. Multivar. Anal. Teng Zhang, Xiuyuan Cheng, Amit Singer
2015	J	`jnl`	Deep Haar Scattering Networks. CoRR Xiuyuan Cheng, Xu Chen, Stéphane Mallat
2015	J	`jnl`	Rotating MaxRS queries. Inf. Sci. Zitong Chen, Yubao Liu, Raymond Chi-Wing Wong, Jiamin Xiong, Xiuyuan Cheng, Peihuan Chen
2014	J	`jnl`	Concentration of the Kirchhoff index for Erdős-Rényi graphs. Syst. Control. Lett. Nicolas Boumal, Xiuyuan Cheng
2014	—	`conf`	Unsupervised Deep Haar Scattering on Graphs. NIPS Xu Chen, Xiuyuan Cheng, Stéphane Mallat
2014	J	`jnl`	Unsupervised Learning by Deep Scattering Contractions. CoRR Xu Chen, Xiuyuan Cheng, Stéphane Mallat
2013	J	`jnl`	Expected performance bounds for estimation on graphs from random relative measurements. CoRR Nicolas Boumal, Xiuyuan Cheng
2010	J	`jnl`	A numerical method for the study of nucleation of ordered phases. J. Comput. Phys. Ling Lin, Xiuyuan Cheng, Weinan E, An-Chang Shi, Pingwen Zhang