SCL Online Seminar by Jelena Smiljanić
You are cordially invited to the SCL online seminar of the Center for the Study of Complex Systems, which will be held on Thursday, 30 September 2021 at 14:00 on Zoom. The talk entitled
Mapping flows in undersampled networks
will be given by Dr. Jelena Smiljanić (Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade and Department of Physics, Umea University, Sweden). Abstract of the talk:
Analyzing flow pathways in networks often highlights subgroups of nodes where flows stay for relatively long times, which indicates that the networks have community structure. Detecting these community patterns is key to revealing critical organizational principles. However, empirical network data often contain measurement errors such as missing links. Uncertainties in the network structure can cause detection of inaccurate community patterns with misleading information about the system. In this talk we will present a community detection method that enables more reliable descriptions of complex systems with incomplete data [1, 2].
[1] J. Smiljanić, D. Edler, and M. Rosvall, Phys. Rev. E 102, 012302 (2020).
[2] J. Smiljanić, C. Blöcker, D. Edler, and M. Rosvall, arXiv:2106.14798 (2021).
Mapping flows in undersampled networks
will be given by Dr. Jelena Smiljanić (Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade and Department of Physics, Umea University, Sweden). Abstract of the talk:
Analyzing flow pathways in networks often highlights subgroups of nodes where flows stay for relatively long times, which indicates that the networks have community structure. Detecting these community patterns is key to revealing critical organizational principles. However, empirical network data often contain measurement errors such as missing links. Uncertainties in the network structure can cause detection of inaccurate community patterns with misleading information about the system. In this talk we will present a community detection method that enables more reliable descriptions of complex systems with incomplete data [1, 2].
[1] J. Smiljanić, D. Edler, and M. Rosvall, Phys. Rev. E 102, 012302 (2020).
[2] J. Smiljanić, C. Blöcker, D. Edler, and M. Rosvall, arXiv:2106.14798 (2021).
