Inverse problems in statistical physics are motivated by the challenges of 'big data'in
different fields, in particular high-throughput experiments in biology. In inverse problems, the …

Learning is a distinctive feature of intelligent behaviour. High-throughput experimental data
and Big Data promise to open new windows on complex systems such as cells, the brain or …

The activity of a neural network is defined by patterns of spiking and silence from the
individual neurons. Because spikes are (relatively) sparse, patterns of activity with …

The joint probability distribution of states of many degrees of freedom in biological systems,
such as firing patterns in neural networks or antibody sequence compositions, often follows …

Zipf's law is just one out of many universal laws proposed to describe statistical regularities
in language. Here we review and critically discuss how these laws can be statistically …

We show that statistical criticality, ie the occurrence of power law frequency distributions,
arises in samples that are maximally informative about the underlying generating process. In …

The concept of resilience occupies an increasingly prominent position within contemporary
efforts to confront many of modernity's most pressing challenges, including global …

Abstract Model-based control of complex systems is a challenging task, particularly when
the system model involves many uncertain elements. To achieve model predictive control of …

Infectious disease epidemics are plaguing the world and a lot of research is focused on the
development of models to reproduce disease dynamics for eco-environmental and …

Complex systems are characterized by a tight, nontrivial interplay of their constituents, which
gives rise to a multiscale spectrum of emergent properties. In this scenario, it is practically …