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mcontisc/README.md

Hi 👋 I am Martina!

I am a postdoctoral researcher at the Department of Network and Data Science at the Central European University (Vienna, Austria).

I completed my Ph.D. in Computer Science at the Max Planck Institute for Intelligent Systems and the University of Tübingen, supervised by Dr. Caterina De Bacco, with a doctoral dissertation entitled "Probabilistic Generative Models for Inference on Complex Systems".

🔍 My research focuses on the development of statistical methods and algorithms to analyze network data.

🔗 If you want to know more about me, check my website: mcontisc.github.io

📫 For any question, please do not hesitate to get in touch at: contiscianim@ceu.edu

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  1. PIHAM PIHAM Public

    Probabilistic generative model to perform inference in attributed multilayer networks, where both edges and attributes can have arbitrary data types.

    Jupyter Notebook 1

  2. MTCOV MTCOV Public

    Probabilistic generative model that incorporates both the topology of interactions and node attributes to extract overlapping communities in directed and undirected multilayer networks.

    Python 41 8

  3. nickruggeri/Hy-MMSBM nickruggeri/Hy-MMSBM Public

    Inference and sampling on the Hy-MMSBM probabilistic model for hypergraphs.

    Python 16 3

  4. Hypergraph-MT Hypergraph-MT Public

    Probabilistic generative model for mixed-membership community detection in hypergraphs, that also allows to infer missing hyperedges of any size in a principled way.

    Jupyter Notebook 23 1

  5. JointCRep JointCRep Public

    Probabilistic generative model for network analysis that takes into account community structure and reciprocity by specifying a closed-form joint distribution of a pair of network edges.

    Jupyter Notebook 4 1

  6. CRep CRep Public

    Probabilistic generative model and efficient algorithm to model reciprocity in directed networks.

    Python 16 2