Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.

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  • The space of functions computed by deep layered machines

    AMA. MozeikaBLDS Physical Review Letters

    Deep layered machines

    The ability of deep neural networks to generalize can be unraveled using path integral methods to compute their typical Boolean functions.

  • Replica analysis of overfitting in generalized linear models

    ACA. CoolenMSAMA. MozeikaFAFAF. Antenucci Journal of Physics A

    Replica analysis of overfitting

    Statistical methods that normally fail for very high-dimensional data can be rescued via mathematical tools from statistical physics.

  • Bayesian networks analysis of malocclusion data

    MSPAGCG. CaldarelliLF Scientific Reports

    Bayesian analysis of medical data

    Bayesian networks describe the evolution of orthodontic features on patients receiving treatment versus no treatment for malocclusion.

  • Quantum generalisation of feedforward neural networks

    KWODO. DahlstenHKRGMK npj Quantum Information

    Quantum neural networks

    We generalise neural networks into a quantum framework, demonstrating the possibility of quantum auto-encoders and teleportation.

  • International Journal of Parallel, Emergent and Distributed Systems

    Memristive networks and learning

    Memristive networks preserve memory and have the ability to learn according to analysis of the network’s internal memory dynamics.

  • Physical Review E

    Dynamics of memristors

    Exact equations of motion provide an analytical description of the evolution and relaxation properties of complex memristive circuits.

  • EPL

    From memory to scale-free

    A local model of preferential attachment with short-term memory generates scale-free networks, which can be readily computed by memristors.

  • PLOS ONE

    Taxonomy and economic growth

    Less developed countries have to learn simple capabilities in order to start a stable industrialization and development process.

  • ESAIM: Proceedings and surveys

    Random graphs with short loops

    The analysis of real networks which contain many short loops requires novel methods, because they break the assumptions of tree-like models.

  • Journal of Physics A

    Entropies of graph ensembles

    Explicit formulae for the Shannon entropies of random graph ensembles provide measures to compare and reproduce their topological features.

  • Journal of Physics A

    Multi-tasking in immune networks

    Associative networks with different loads model the ability of the immune system to respond simultaneously to multiple distinct antigen invasions.

  • Journal of Physics A

    Tailored random graph ensembles

    New mathematical tools quantify the topological structure of large directed networks which describe how genes interact within a cell.