11 October 2016, Tuesday: 08:55-12:00 (conference room 6420 of New Building)
08:55 -- 09:00 Opening remarks
09:00 -- 09:45 Dr. Tatsuro Kawamoto (AIST, Japan)
Cross-validation estimate of the number of modules in modular networks
It is a common and important task to extract modular structures from network data. Whereas many papers have been published in the field of computer science and statistical physics, there are many problems remain mystery, particularly for sparse networks. Here we focus on the model selection problem, i.e., the selection of the number of modules. We show that the leave-one-out cross-validation estimate of prediction errors are good measures to determine the number of modules and can be efficiently calculated using belief propagation.
09:50 -- 10:35 Dr. Yingying Xu (Aalto University, Finland)
Statistical inference of genome-wide epistasis in bacteria and general discussions
Potts model in statistical physics has extended its application to biological data in last decay. After great success in prediction of protein structures, Direct Coupling Analysis is tried on genome-wide epistasis inference in bacteria in our research. We will show the results on the major human pathogen Streptococcus pneumonia. However, there are still many interesting open questions on the methodology part, such as how to determine the significant coupling threshold. In the talk, I will present the questions as well and let's have a look together.
11:00 -- 11:50 Prof. Erik Aurell (KTH, Sweden)
A global view of quantum computation with noisy components
This talk is an attempt to estimate the error made in a general quantum computation by the Feynman-Vernon method. I will show how some simple estimates can be obtained for idealized systems, and why such estimates are more difficult to obtain for more advanced schemes such as surface codes. The talk is mainly based onarXiv:1606.09407.