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.
Machine learning techniques enhance the efficiency of energy harvesters by implementing reversible energy-conserving operations.
Bayesian networks describe the evolution of orthodontic features on patients receiving treatment versus no treatment for malocclusion.
An adaptive network of oscillators in fragmented and incoherent states can re-organise itself into connected and synchronized states.
Time series data from networks of credit default swaps display no early warnings of financial crises without additional macroeconomic indicators.
The likelihood of stock prices bouncing on specific values increases due to memory effects in the time series data of the price dynamics.
The optimal architecture of a financial system is only dependent on its topology when the market is illiquid, and no topology is always superior.
Complex networks detect the driver institutions of an interbank market and ascertain that intervention policies should be time-scale dependent.
A quantitative assessment of the non-monetary advantage of diversification represents a country’s hidden potential for development and growth.