HIGHLIGHTS
Bayesian estimation of information-theoretic metrics for sparsely sampled distributions
Chaos, Solitons & Fractals - Feb. 7, 2024
Estimating the Shannon entropy of a discrete distribution from which we have only observed a small sample is challenging. Estimating other information-theoretic metrics, such as the Kullback–Leibler divergence between two sparsely sampled discrete distributions, is even harder. Here, we propose a fast, semi-analytical estimator for sparsely sampled distributions. Its derivation...
Hyperedge prediction and the statistical mechanisms of higher-order and lower-order interactions in complex networks
Proc. Natl. Acad. Sci. USA - Dec. 7, 2023
Complex networked systems often exhibit higher-order interactions, beyond dyadic interactions, which can dramatically alter their observed behavior. Consequently, understanding hypergraphs from a structural perspective has become increasingly important. Statistical, group-based inference approaches are well suited for unveiling the underlying community structure and predicting unobserved interactions. However, these approaches often rely...
Differences in collaboration structures and impact among prominent researchers in Europe and North America
EPJ Data Sci. - April 28, 2023
Scientists collaborate through intricate networks, which impact the quality and scope of their research. At the same time, funding and institutional arrangements, as well as scientific and political cultures, affect the structure of collaboration networks. Since such arrangements and cultures differ across regions in the world in systematic ways, we...
OUR RESEARCH
Complex Systems
Cells, ecosystems and economies are examples of complex systems. In complex systems, individual components interact with each other, usually in nonlinear ways, giving rise to complex networks of interactions that are neither totally regular nor totally random. Partly because of the interactions themselves and partly because of the interaction's topology, complex systems cannot be properly understood by just analyzing their constituent parts.
Data Science
Humans generate information at an unprecedented pace, with some estimates suggesting that, in a year, we now produce on the order of 10^21 bytes of data, millions of times the amount of information in all the books ever written. Processing this "data deluge", as some have called it, requires new tools and new approaches at the interface of statistics, statistical and machine learning, network theory and statistical physics.
Multidisciplinarity
Our goal is to push forward the boundaries of science. We are interested in addressing fundamental questions in all areas of science including natural, social and economic sciences. We put a special emphasis in the development of tools that aid scientific discovery through understanding and quantification of a specific phenomenon. To this end we have assembled a multidisciplinary team and have established solid collaborations with experts in biology, social sciences, ecology and economics.