Lizhen Lin - RankMe

50 papers A* 4B 1Journal 39Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Flow Matching is Adaptive to Manifold Structures. CoRR Shivam Kumar, Yixin Wang, Lizhen Lin
2025	A*	`conf`	A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models. ICML Shivam Kumar, Yun Yang, Lizhen Lin
2025	J	`jnl`	Accelerated algorithms for convex and non-convex optimization on manifolds. Mach. Learn. Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson
2025	A*	`conf`	Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation. ICLR Rong Tang, Lizhen Lin, Yun Yang
2025	J	`jnl`	Posterior Contraction for Sparse Neural Networks in Besov Spaces with Intrinsic Dimensionality. CoRR Kyeongwon Lee, Lizhen Lin, Jaewoo Park, Seonghyun Jeong
2025	J	`jnl`	Robust and Scalable Variational Bayes. CoRR Carlos Misael Madrid Padilla, Shitao Fan, Lizhen Lin
2024	J	`jnl`	A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models. CoRR Shivam Kumar, Yun Yang, Lizhen Lin
2024	J	`jnl`	A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks. Trans. Mach. Learn. Res. Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin
2024	J	`jnl`	Classification of Directed Networks With Application to Neuroimaging Data. IEEE Access Li Chen, Yuncheng Liu, Lizhen Lin, Dongpei Zhang
2023	J	`jnl`	A Bayesian sparse factor model with adaptive posterior concentration. CoRR Ilsang Ohn, Lizhen Lin, Yongdai Kim
2023	J	`jnl`	A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. J. Mach. Learn. Res. Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
2023	J	`jnl`	A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks. CoRR Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin
2023	J	`jnl`	Extrinsic Bayesian Optimization on Manifolds. Algorithms Yihao Fang, Mu Niu, Pokman Cheung, Lizhen Lin
2023	J	`jnl`	Intrinsic and extrinsic deep learning on manifolds. CoRR Yihao Fang, Ilsang Ohn, Vijay Gupta, Lizhen Lin
2023	J	`jnl`	Machine Learning and the Future of Bayesian Computation. CoRR Steven Winter, Trevor Campbell, Lizhen Lin, Sanvesh Srivastava, David B. Dunson
2023	J	`jnl`	Nested stochastic block model for simultaneously clustering networks and nodes. CoRR Nathaniel Josephs, Arash A. Amini, Marina S. Paez, Lizhen Lin
2022	—	`conf`	A Topological Characterization of DNA Sequences Based on Chaos Geometry and Persistent Homology. CSCI Dong Quan Ngoc Nguyen, Phuong Dong Tan Le, Lin Xing, Lizhen Lin
2022	J	`jnl`	A graph-theoretical approach to DNA similarity analysis. Commun. Inf. Syst. Dong Quan Ngoc Nguyen, Lin Xing, Phuong Dong Tan Le, Lizhen Lin
2022	J	`jnl`	Bayesian community detection for networks with covariates. CoRR Luyi Shen, Arash A. Amini, Nathaniel Josephs, Lizhen Lin
2022	J	`jnl`	Extrinsic Bayesian Optimizations on Manifolds. CoRR Yihao Fang, Mu Niu, Pokman Cheung, Lizhen Lin
2022	J	`jnl`	Learning Subspaces of Different Dimensions. J. Comput. Graph. Stat. Brian St. Thomas, Kisung You, Lizhen Lin, Lek-Heng Lim, Sayan Mukherjee
2022	B	`conf`	Network Distance based on Laplacian Flows on Graphs. IEEE Big Data Dianbin Bao, Kisung You, Lizhen Lin
2022	J	`jnl`	Neural-PDE: a RNN based neural network for solving time dependent PDEs. Commun. Inf. Syst. Yihao Hu, Tong Zhao, Shixin Xu, Lizhen Lin, Zhiliang Xu
2022	J	`jnl`	Robustness Against Adversarial Attacks in Neural Networks Using Incremental Dissipativity. IEEE Control. Syst. Lett. Bernardo Aquino, Arash Rahnama, Peter J. Seiler, Lizhen Lin, Vijay Gupta
2021	J	`jnl`	A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. CoRR Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
2021	J	`jnl`	Robustness against Adversarial Attacks in Neural Networks using Incremental Dissipativity. CoRR Bernardo Aquino, Arash Rahnama, Peter Seiler, Lizhen Lin, Vijay Gupta
2021	—	`conf`	Training Graph Neural Networks by Graphon Estimation. IEEE BigData Ziqing Hu, Yihao Fang, Lizhen Lin
2021	J	`jnl`	Training Graph Neural Networks by Graphon Estimation. CoRR Ziqing Hu, Yihao Fang, Lizhen Lin
2020	J	`jnl`	A Hypothesis Testing for Large Weighted Networks With Applications to Functional Neuroimaging Data. IEEE Access Li Chen, Lizhen Lin, Jie Zhou
2020	J	`jnl`	Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds. CoRR Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson
2020	—	`conf`	Community Detection, Pattern Recognition, and Hypergraph-Based Learning: Approaches Using Metric Geometry and Persistent Homology. FSDM Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
2020	J	`jnl`	Community detection, pattern recognition, and hypergraph-based learning: approaches using metric geometry and persistent homology. CoRR Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
2020	J	`jnl`	Neural Time-Dependent Partial Differential Equation. CoRR Yihao Hu, Tong Zhao, Zhiliang Xu, Lizhen Lin
2020	—	`conf`	Optimization of Graph Neural Networks with Natural Gradient Descent. IEEE BigData Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson, Lizhen Lin
2020	J	`jnl`	Optimization of Graph Neural Networks with Natural Gradient Descent. CoRR Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson, Lizhen Lin
2020	—	`conf`	Weight Prediction for Variants of Weighted Directed Networks. IEEE BigData Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
2020	J	`jnl`	Weight Prediction for Variants of Weighted Directed Networks. CoRR Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
2019	J	`jnl`	Exact slice sampler for Hierarchical Dirichlet Processes. CoRR Arash A. Amini, Marina S. Paez, Lizhen Lin, Zahra S. Razaee
2019	J	`jnl`	Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks. CoRR Marina S. Paez, Arash A. Amini, Lizhen Lin
2018	A*	`conf`	Communication Efficient Parallel Algorithms for Optimization on Manifolds. NeurIPS Bayan Saparbayeva, Michael Minyi Zhang, Lizhen Lin
2018	J	`jnl`	Communication Efficient Parallel Algorithms for Optimization on Manifolds. CoRR Bayan Saparbayeva, Michael Minyi Zhang, Lizhen Lin
2018	J	`jnl`	Intrinsic Gaussian processes on complex constrained domains. CoRR Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson
2018	J	`jnl`	Network Distance Based on Laplacian Flows on Graphs. CoRR Dianbin Bao, Kisung You, Lizhen Lin
2018	J	`jnl`	Robust and parallel Bayesian model selection. Comput. Stat. Data Anal. Michael Minyi Zhang, Henry Lam, Lizhen Lin
2017	—	`conf`	On clustering network-valued data. NIPS Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin
2017	J	`jnl`	Robust and Scalable Bayes via a Median of Subset Posterior Measures. J. Mach. Learn. Res. Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2017	J	`jnl`	Scale and curvature effects in principal geodesic analysis. J. Multivar. Anal. Drew Lazar, Lizhen Lin
2014	J	`jnl`	Robust and scalable Bayes via a median of subset posterior measures. CoRR Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2014	A*	`conf`	Scalable and Robust Bayesian Inference via the Median Posterior. ICML Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
2013	J	`jnl`	Recent progress in the nonparametric estimation of monotone curves - With applications to bioassay and environmental risk assessment. Comput. Stat. Data Anal. Rabi Bhattacharya, Lizhen Lin