Statistical Inference, Learning and Optimization for Dynamics on Networks

Hello NetFOLLOWERS! Last Thursday Dr. Mateusz Wilinski from Los Alamos National Laboratory introduced us the powerful dynamic message-passing (DMP) algorithm, that makes possible to complete inference task on large networks and can be used on optimisation problems as well.

He showed an application of DMP method on Independent Cascade model to infer the marginal probability defined on the nodes of the network, which has an extraordinary low computational complexity - comparable with a single Monte Carlo run!

In the second part of his talk, he shared with us his frustrating experience of applying for a grant, and encouraged the audience in the same situation: the application process may contain lots of randomness and do not feel discouragement if the process does not go well.

The talk is available on our YouTube channel. What do you think about grants applications? Have you ever apply for grants and successfully received the prize? Let us know on our Blog thread (Twitter)!