Probing the Geometry of Data with Diffusion Fr\'echet Functions

@article{Martinez2016ProbingTG,
  title={Probing the Geometry of Data with Diffusion Fr\'echet Functions},
  author={D. Mart'inez and Christine H. Lee and P. Kim and W. Mio},
  journal={arXiv: Machine Learning},
  year={2016}
}
Many complex ecosystems, such as those formed by multiple microbial taxa, involve intricate interactions amongst various sub-communities. The most basic relationships are frequently modeled as co-occurrence networks in which the nodes represent the various players in the community and the weighted edges encode levels of interaction. In this setting, the composition of a community may be viewed as a probability distribution on the nodes of the network. This paper develops methods for modeling… Expand

Figures and Tables from this paper

Persistence homology of networks: methods and applications
Graph Classification via Heat Diffusion on Simplicial Complexes
A topological study of functional data and Fréchet functions of metric measure spaces
Classification of Turkish makam music: a topological approach
Text Classification via Network Topology: A Case Study on the Holy Quran
  • M. Aktas, Esra Akbas
  • Computer Science
  • 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA)
  • 2019
The phylogenetic LASSO and the microbiome
Decorated Merge Trees for Persistent Topology

References

SHOWING 1-10 OF 30 REFERENCES
Nonparametric Sparsification of Complex Multiscale Networks
Graph Wavelets for Multiscale Community Mining
Diffusion maps
Exploring network structures in feature space
Exploring Network Structure, Dynamics, and Function using NetworkX
Topology and data
...
1
2
3
...