Lizhen Lin

Orcid: 0000-0002-7913-2780

According to our database1, Lizhen Lin authored at least 31 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Extrinsic Bayesian Optimization on Manifolds.
Algorithms, February, 2023

A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models.
J. Mach. Learn. Res., 2023

Nested stochastic block model for simultaneously clustering networks and nodes.
CoRR, 2023

A Bayesian sparse factor model with adaptive posterior concentration.
CoRR, 2023

Machine Learning and the Future of Bayesian Computation.
CoRR, 2023

A Semi-Bayesian Nonparametric Hypothesis Test Using Maximum Mean Discrepancy with Applications in Generative Adversarial Networks.
CoRR, 2023

Intrinsic and extrinsic deep learning on manifolds.
CoRR, 2023

2022
Learning Subspaces of Different Dimensions.
J. Comput. Graph. Stat., January, 2022

Robustness Against Adversarial Attacks in Neural Networks Using Incremental Dissipativity.
IEEE Control. Syst. Lett., 2022

Extrinsic Bayesian Optimizations on Manifolds.
CoRR, 2022

Bayesian community detection for networks with covariates.
CoRR, 2022

A graph-theoretical approach to DNA similarity analysis.
Commun. Inf. Syst., 2022

Neural-PDE: a RNN based neural network for solving time dependent PDEs.
Commun. Inf. Syst., 2022

Network Distance based on Laplacian Flows on Graphs.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Training Graph Neural Networks by Graphon Estimation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds.
CoRR, 2020

Neural Time-Dependent Partial Differential Equation.
CoRR, 2020

A Hypothesis Testing for Large Weighted Networks With Applications to Functional Neuroimaging Data.
IEEE Access, 2020

Community Detection, Pattern Recognition, and Hypergraph-Based Learning: Approaches Using Metric Geometry and Persistent Homology.
Proceedings of the Fuzzy Systems and Data Mining VI, 2020

Weight Prediction for Variants of Weighted Directed Networks.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Optimization of Graph Neural Networks with Natural Gradient Descent.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks.
CoRR, 2019

Exact slice sampler for Hierarchical Dirichlet Processes.
CoRR, 2019

2018
Robust and parallel Bayesian model selection.
Comput. Stat. Data Anal., 2018

Intrinsic Gaussian processes on complex constrained domains.
CoRR, 2018

Communication Efficient Parallel Algorithms for Optimization on Manifolds.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Scale and curvature effects in principal geodesic analysis.
J. Multivar. Anal., 2017

Robust and Scalable Bayes via a Median of Subset Posterior Measures.
J. Mach. Learn. Res., 2017

On clustering network-valued data.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2014
Scalable and Robust Bayesian Inference via the Median Posterior.
Proceedings of the 31th International Conference on Machine Learning, 2014

2013
Recent progress in the nonparametric estimation of monotone curves - With applications to bioassay and environmental risk assessment.
Comput. Stat. Data Anal., 2013


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