Introducing Logic-based Integrative Causal Discovery

Prof. Tsamardinos will present the field of logic-based integrative causal discovery during two different talks to be held in Paris, France, in the upcoming week. The talks will illustrate the characteristics of a new, logic-based approach to causal discovery, that has been partly pioneered by our group. This approach is more robust to statistical errors, makes more […]

MXM invited talk at ELIXIR meeting

ELIXIR is an inter-governmental organisation which builds on existing data resources and services within Europe. Its main objective is orchestrating the collection, quality control and archiving of large amounts of biological data produced by life science experiments. Prof. Tsamardinos will give an invited talk at the forthcoming meeting “In silico infrastructures for Life Science’s Big Data – and the […]

Talk announcement of Prof Jan Lemeire February 16th room A113 CSD at 10:00

title: “Causal structure learning under unfaithfulness.”   abstract:” Inferring from experimental data the causal relations among variables is a scientific important but challenging task. One of the approaches relies on the probabilistic independencies between variables. Algorithms have been designed that allow the construction of the causal model of the system. Although powerful, one of the fundamental […]

Invited speech by Yannis Pantazis

Between January 19 – 22, 2016, Yannis Pantazis attended as an invited speaker the “Uncertainty Quantification for Multiscale Stochastic Systems and Applications” workshop held at IPAM, UCLA. The title of the talk was “Sensitivity analysis, uncertainty quantification and inference in stochastic dynamics“.