Here is a list of peer-review publications:

1. Diffusion by exchange in HB-graphs

Authors: Xavier Ouvrard, Jean-Marie Le Goff, Stéphane Marchand-Maillet

CBMI 2018 La Rochelle (France): published on IEEE Xplore DOI: 10.1109/CBMI.2018.8516525

2. Hypergraph Modeling and Visualisation of Complex Co-occurence Networks

Authors: Xavier Ouvrard, Jean-Marie Le Goff, Stéphane Marchand-Maillet

IMA 2nd TCDM 2018 Derby (UK): published in ENDM Elsevier DOI: 10.1016/j.endm.2018.11.011

3. On Adjacency and e-Adjacency in General Hypergraphs: Towards a New e-Adjacency Tensor

Authors: Xavier Ouvrard, Jean-Marie Le Goff, Stéphane Marchand-Maillet

IMA 2nd TCDM 2018 Derby (UK): published in ENDM Elsevier DOI: 10.1016/j.endm.2018.11.012

  1. arXiv:1905.11695  [pdfother

    The HyperBagGraph DataEdron: An Enriched Browsing Experience of Multimedia Datasets

    Authors: Xavier OuvrardJean-Marie Le GoffStéphane Marchand-Maillet

    AbstractTraditional verbatim browsers give back information in a linear way according to a ranking performed by a search engine that may not be optimal for the surfer. The latter may need to assess the pertinence of the information retrieved, particularly when she wants to explore other facets of a multi-facetted information space. For instance, in a multimedia dataset different facets such as keyw… ▽ More

    Submitted 28 May, 2019; originally announced May 2019.

    Comments: Extension of the hypergraph framework shortly presented in arXiv:1809.00164 (possible small overlaps); use the theoretical framework of hb-graphs presented in arXiv:1809.00190

  2. Exchange-Based Diffusion in Hb-Graphs: Highlighting Complex Relationships

    Authors: Xavier OuvrardJean-Marie Le GoffStephane Marchand-Maillet

    AbstractMost networks tend to show complex and multiple relationships between entities. Networks are usually modeled by graphs or hypergraphs; nonetheless a given entity can occur many times in a relationship: this brings the need to deal with multisets instead of sets or simple edges. Diffusion processes are useful to highlight interesting parts of a network: they usually start with a stroke at one verte… ▽ More

    Submitted 28 May, 2019; v1 submitted 1 September, 2018; originally announced September 2018.

    Comments: arXiv:1809.00190v1: Accepted version of article submitted at CBMI 2018 IEEE This version is an extended version of arXiv:1809.00190v1 currently in submission

  3. Hypergraph Modeling and Visualisation of Complex Co-occurence Networks

    Authors: Xavier OuvrardJean-Marie Le GoffStephane Marchand-Maillet

    AbstractFinding inherent or processed links within a dataset allows to discover potential knowledge. The main contribution of this article is to define a global framework that enables optimal knowledge discovery by visually rendering co-occurences (i.e. groups of linked data instances attached to a metadata reference) - either inherently present or processed - from a dataset as facets. Hypergraphs are wel… ▽ More

    Submitted 1 September, 2018; originally announced September 2018.

    Comments: Preprint submitted at ENDM Special Journal 2nd IMA Conference on Theoretical and Computational Discrete Mathematic

  4. arXiv:1809.00162  [pdfpsother

     
    math.CO cs.DM

    On Adjacency and e-Adjacency in General Hypergraphs: Towards a New e-Adjacency Tensor

    Authors: Xavier OuvrardJean-Marie Le GoffStephane Marchand-Maillet

    AbstractIn graphs, the concept of adjacency is clearly defined: it is a pairwise relationship between vertices. Adjacency in hypergraphs has to integrate hyperedge multi-adicity: the concept of adjacency needs to be defined properly by introducing two new concepts: k-adjacency - k vertices are in the same hyperedge - and e-adjacency - vertices of a given hyperedge are e-adjacent. In order to build a n… ▽ More

    Submitted 1 September, 2018; originally announced September 2018.

    Comments: Preprint submitted to ENDM special journal 2nd IMA Conference on Theoretical and Computational Discrete Mathematics

  5. Adjacency and Tensor Representation in General Hypergraphs.Part 2: Multisets, Hb-graphs and Related e-adjacency Tensors

    Authors: Xavier OuvrardJean-Marie Le GoffStephane Marchand-Maillet

    AbstractHyperBagGraphs (hb-graphs as short) extend hypergraphs by allowing the hyperedges to be multisets. Multisets are composed of elements that have a multiplicity. When this multiplicity has positive integer values, it corresponds to non ordered lists of potentially duplicated elements. We define hb-graphs as family of multisets over a vertex set; natural hb-graphs correspond to hb-graphs that have mu… ▽ More

    Submitted 18 September, 2018; v1 submitted 30 May, 2018; originally announced May 2018.

  6. Adjacency and Tensor Representation in General Hypergraphs Part 1: e-adjacency Tensor Uniformisation Using Homogeneous Polynomials

    Authors: Xavier OuvrardJean-Marie Le GoffStéphane Marchand-Maillet

    AbstractAdjacency between two vertices in graphs or hypergraphs is a pairwise relationship. It is redefined in this article as 2-adjacency. In general hypergraphs, hyperedges hold for n-adic relationship. To keep the n-adic relationship the concepts of k-adjacency and e-adjacency are defined. In graphs 2-adjacency and e-adjacency concepts match, just as k-adjacency and e-adjacency do for k-unifo… ▽ More

    Submitted 30 May, 2018; v1 submitted 21 December, 2017; originally announced December 2017.

  7. arXiv:1707.00115  [pdfother

    Networks of Collaborations: Hypergraph Modeling and Visualisation

    Authors: Xavier OuvrardJean-Marie Le GoffStéphane Marchand-Maillet

    AbstractThe acknowledged model for networks of collaborations is the hypergraph model. Nonetheless when it comes to be visualized hypergraphs are transformed into simple graphs. Very often, the transformation is made by clique expansion of the hyperedges resulting in a loss of information for the user and in artificially more complex graphs due to the high number of edges represented. The extra-node repre… ▽ More

    Submitted 1 July, 2017; originally announced July 2017.

    Comments: 24 pages, 9 figure

Here are a bunch of posters presented in different places:

07.2019: SIAM-ICIAM, Valencia (Spain): The HyperBagGraph DataEdron: An Enriched Experience of Scientific Publications (modified version)

05.2019: Critical and Collective Effects in Graphs and Networks, School of Physics, Les Houches (France): Hb-graphs and their applications & The HyperBagGraph DataEdron: An Enriched Experience of Scientific Publications

01.2019: Application Machine Learning Days, Lausanne (Switzerland): The HyperBagGraph DataEdron:  An Enriched Experience of Scientific Publications

09.2018: IMA 2nd TCDM Conference, Derby (UK): Hypergraph Modeling and Visualisation of Complex Co-occurences Networks

04.2018: CERN Doctoral Student Poster Session, Meyrin (Switzerland): Hypergraph Modeling and Visualisation of Complex Collaboration Networks

01.2018: CUSO Winter School, Champery (Switzerland): Improve Visual and Human Understanding of Big Data using Graph/Hypergraph-based visualisations

01.2017: CUSO Winter School, Champery (Switzerland): Improve Visual and Human Understanding of Big Data using Graph/Hypergraph-based visualisations