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Chair of Statistical Data Science

The Statistical Data Science (SDS) group is led by professor Sofia Olhede. Data Science concerns the appropriate way to analyse and thus understand the large volumes of data that are being generated in most parts of society every minute. The SDS group is in particular interested in temporal, spatial and relational data. The group has developed methods to analyse large collections of oceanographic and geophysical data sets, as well as ecological data. Prof Olhede also has an interest in data taking the form of locations, as well as relational data (networks). The group has shown that any network can be well-approximated by using a model with a large number of groups, where all the members of a group interact the same way. The group also has a strong interest in data governance and data ethics.

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  1. NetworkHistogram.jl NetworkHistogram.jl Public

    Network Histogram method for approximating graphons

    Julia 4

  2. nethist nethist Public

    Forked from EnigmaSong/nethist

    R package for Network histogram

    R

  3. PointProcessFilters.jl PointProcessFilters.jl Public

    Julia package for filtering point processes

    Julia

Repositories

Showing 5 of 5 repositories
  • PointProcessFilters.jl Public

    Julia package for filtering point processes

    SDS-EPFL/PointProcessFilters.jl’s past year of commit activity
    Julia 0 MIT 0 1 0 Updated Jan 7, 2025
  • NetworkHistogram.jl Public

    Network Histogram method for approximating graphons

    SDS-EPFL/NetworkHistogram.jl’s past year of commit activity
    Julia 4 MIT 0 1 1 Updated Jan 6, 2025
  • SDS-EPFL/CodeFor-VisualizingTheWavenumberContentOfAPointPattern’s past year of commit activity
    Julia 0 MIT 0 0 0 Updated Aug 16, 2023
  • .github Public
    SDS-EPFL/.github’s past year of commit activity
    0 0 0 0 Updated Apr 12, 2023
  • nethist Public Forked from EnigmaSong/nethist

    R package for Network histogram

    SDS-EPFL/nethist’s past year of commit activity
    R 0 1 0 0 Updated Apr 11, 2023

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