A list of non-exhaustive relevant topics include:

- Models and measures for multiplex  & attributed networks.

- Co-evolution of layers in multiplex networks.

- Layer aggregation approaches.

- Vertex similarity in multiplex and attributed networks

- Community detection in multiplex network & attributed networks.

-  Link prediction in multiplex and attributed networks

- Multiplex and attributed networks evolution models

- Multiplex network and dynamic network mining

- Ensemble learning for multiplex and attributed networks mining

- Multiplex and attributed networks visualisation.

- Applications of multiplex network mining and modeling.

- Mining and learning in augmented graphs

- Modeling and visualizing of augmented graphs

- Constraint-based pattern mining in augmented graphs

- Computational or statistical learning theory related to augmented graphs

- Analysis of heterogeneous network

- Analysis of multidimensional graphs

- Relationships between augmented graphs and statistical relational learning or inductive logic programming