Corpus ID: 44395802

Computational Topology in

@inproceedings{Stolz2014ComputationalTI,
  title={Computational Topology in},
  author={Bernadette J. Stolz},
  year={2014}
}
  • Bernadette J. Stolz
  • Published 2014
  • Computational topology is a set of algorithmic methods developed to understand topological invariants such as loops and holes in high-dimensional data sets. In particular, a method know as persistent homology has been used to understand such shapes and their persistence in point clouds and networks. It has only been applied to neuronal networks in recent years. While most tools from network science focus solely on local properties based on pairwise connections, the topological tools reveal more… CONTINUE READING
    4 Citations
    The importance of the whole: Topological data analysis for the network neuroscientist
    • 46
    • PDF
    Two’s company, three (or more) is a simplex
    • 135
    • PDF
    Closures and Cavities in the Human Connectome
    • 19
    • PDF

    References

    SHOWING 1-10 OF 29 REFERENCES
    jHoles: A Tool for Understanding Biological Complex Networks via Clique Weight Rank Persistent Homology
    • 48
    • Highly Influential
    • PDF
    Persistent Homology — a Survey
    • 559
    • PDF
    Discriminative persistent homology of brain networks
    • 75
    • PDF
    Barcodes: The persistent topology of data
    • 746
    • Highly Influential
    • PDF
    javaPlex: A Research Software Package for Persistent (Co)Homology
    • 207
    Networks: An Introduction
    • 8,391
    Topology and data
    • 1,373
    • PDF
    Weighted Functional Brain Network Modeling via Network Filtration
    • 13
    • Highly Influential
    • PDF
    A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology
    • 153
    • PDF
    Topological persistence and simplification
    • 724