Lizhen Lin

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 38

Top Topics

Bayesian Model Selection

Gaussian Process

Hypothesis Test

Top Venues

J. Mach. Learn. Res.

Commun. Inf. Syst.

Publications

Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models. J. Mach. Learn. Res. 24 (2023)
Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin
A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks. CoRR (2023)
Steven Winter, Trevor Campbell, Lizhen Lin, Sanvesh Srivastava, David B. Dunson
Machine Learning and the Future of Bayesian Computation. CoRR (2023)
Nathaniel Josephs, Arash A. Amini, Marina S. Paez, Lizhen Lin
Nested stochastic block model for simultaneously clustering networks and nodes. CoRR (2023)
Yihao Fang, Mu Niu, Pokman Cheung, Lizhen Lin
Extrinsic Bayesian Optimization on Manifolds. Algorithms 16 (2) (2023)
Yihao Fang, Ilsang Ohn, Vijay Gupta, Lizhen Lin
Intrinsic and extrinsic deep learning on manifolds. CoRR (2023)
Ilsang Ohn, Lizhen Lin, Yongdai Kim
A Bayesian sparse factor model with adaptive posterior concentration. CoRR (2023)
Luyi Shen, Arash A. Amini, Nathaniel Josephs, Lizhen Lin
Bayesian community detection for networks with covariates. CoRR (2022)
Dianbin Bao, Kisung You, Lizhen Lin
Network Distance based on Laplacian Flows on Graphs. Big Data (2022)
Yihao Fang, Mu Niu, Pokman Cheung, Lizhen Lin
Extrinsic Bayesian Optimizations on Manifolds. CoRR (2022)
Dong Quan Ngoc Nguyen, Phuong Dong Tan Le, Lin Xing, Lizhen Lin
A Topological Characterization of DNA Sequences Based on Chaos Geometry and Persistent Homology. CSCI (2022)
Dong Quan Ngoc Nguyen, Lin Xing, Phuong Dong Tan Le, Lizhen Lin
A graph-theoretical approach to DNA similarity analysis. Commun. Inf. Syst. 22 (3) (2022)
Bernardo Aquino, Arash Rahnama, Peter J. Seiler, Lizhen Lin, Vijay Gupta
Robustness Against Adversarial Attacks in Neural Networks Using Incremental Dissipativity. IEEE Control. Syst. Lett. 6 (2022)
Yihao Hu, Tong Zhao, Shixin Xu, Lizhen Lin, Zhiliang Xu
Neural-PDE: a RNN based neural network for solving time dependent PDEs. Commun. Inf. Syst. 22 (2) (2022)
Brian St. Thomas, Kisung You, Lizhen Lin, Lek-Heng Lim, Sayan Mukherjee
Learning Subspaces of Different Dimensions. J. Comput. Graph. Stat. 31 (1) (2022)
Bernardo Aquino, Arash Rahnama, Peter J. Seiler, Lizhen Lin, Vijay Gupta
Robustness against Adversarial Attacks in Neural Networks using Incremental Dissipativity. CoRR (2021)
Minwoo Chae, Dongha Kim, Yongdai Kim, Lizhen Lin
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models. CoRR (2021)
Ziqing Hu, Yihao Fang, Lizhen Lin
Training Graph Neural Networks by Graphon Estimation. CoRR (2021)
Ziqing Hu, Yihao Fang, Lizhen Lin
Training Graph Neural Networks by Graphon Estimation. IEEE BigData (2021)
Yihao Hu, Tong Zhao, Zhiliang Xu, Lizhen Lin
Neural Time-Dependent Partial Differential Equation. CoRR (2020)
Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
Weight Prediction for Variants of Weighted Directed Networks. CoRR (2020)
Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson, Lizhen Lin
Optimization of Graph Neural Networks with Natural Gradient Descent. CoRR (2020)
Li Chen, Lizhen Lin, Jie Zhou
A Hypothesis Testing for Large Weighted Networks With Applications to Functional Neuroimaging Data. IEEE Access 8 (2020)
Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson
Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds. CoRR (2020)
Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
Community detection, pattern recognition, and hypergraph-based learning: approaches using metric geometry and persistent homology. CoRR (2020)
Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
Weight Prediction for Variants of Weighted Directed Networks. IEEE BigData (2020)
Mohammad Rasool Izadi, Yihao Fang, Robert Stevenson, Lizhen Lin
Optimization of Graph Neural Networks with Natural Gradient Descent. IEEE BigData (2020)
Dong Quan Ngoc Nguyen, Lin Xing, Lizhen Lin
Community Detection, Pattern Recognition, and Hypergraph-Based Learning: Approaches Using Metric Geometry and Persistent Homology. FSDM (2020)
Marina S. Paez, Arash A. Amini, Lizhen Lin
Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks. CoRR (2019)
Arash A. Amini, Marina S. Paez, Lizhen Lin, Zahra S. Razaee
Exact slice sampler for Hierarchical Dirichlet Processes. CoRR (2019)
Bayan Saparbayeva, Michael Minyi Zhang, Lizhen Lin
Communication Efficient Parallel Algorithms for Optimization on Manifolds. NeurIPS (2018)
Michael Minyi Zhang, Henry Lam, Lizhen Lin
Robust and parallel Bayesian model selection. Comput. Stat. Data Anal. 127 (2018)
Bayan Saparbayeva, Michael Minyi Zhang, Lizhen Lin
Communication Efficient Parallel Algorithms for Optimization on Manifolds. CoRR (2018)
Dianbin Bao, Kisung You, Lizhen Lin
Network Distance Based on Laplacian Flows on Graphs. CoRR (2018)
Mu Niu, Pokman Cheung, Lizhen Lin, Zhenwen Dai, Neil D. Lawrence, David B. Dunson
Intrinsic Gaussian processes on complex constrained domains. CoRR (2018)
Drew Lazar, Lizhen Lin
Scale and curvature effects in principal geodesic analysis. J. Multivar. Anal. 153 (2017)
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
Robust and Scalable Bayes via a Median of Subset Posterior Measures. J. Mach. Learn. Res. 18 (2017)
Soumendu Sundar Mukherjee, Purnamrita Sarkar, Lizhen Lin
On clustering network-valued data. NIPS (2017)
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
Robust and scalable Bayes via a median of subset posterior measures. CoRR (2014)
Stanislav Minsker, Sanvesh Srivastava, Lizhen Lin, David B. Dunson
Scalable and Robust Bayesian Inference via the Median Posterior. ICML (2014)
Rabi Bhattacharya, Lizhen Lin
Recent progress in the nonparametric estimation of monotone curves - With applications to bioassay and environmental risk assessment. Comput. Stat. Data Anal. 63 (2013)