Topological Learning for Motion Data via Mixed Coordinates-Reference-Cited by-同舟云学术

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Topological Learning for Motion Data via Mixed Coordinates

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Big Data (Big Data)
language:
Short-container-title:

Author:

Luo Hengrui¹,Kim Jisu²,Patania Alice³,Vejdemo-Johansson Mikael⁴

Affiliation:

1. Lawrence Berkeley National Laboratory

2. DataShape Team, Inria Saclay, and LMO, Université Paris-Saclay

3. University of Vermont,Department of Mathematics and Statistics

4. CUNY College of Staten Island, and Computer Science Program, CUNY Graduate Center,Department of Mathematics

Funder

Office of Science

U.S. Department of Energy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9671263/9671273/09671525.pdf?arnumber=9671525

Reference27 articles.

1. Periodic motion embedded in plane Couette turbulence: regeneration cycle and burst

2. Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing

3. Independent component analysis: recent advances

4. Persistent Cohomology and Circular Coordinates

5. Generalized penalty for circular coordinate representation

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Asymptotics of lower dimensional zero-density regions;Statistics;2023-09-25

2. Combining Geometric and Topological Information for Boundary Estimation;2021 IEEE International Conference on Big Data (Big Data);2021-12-15

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