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Physical Review. E|September 27, 2018
Analytical approach to network inference: Investigating degree distributionGloria Cecchini, Björn SchelterJournal of Neuroscience Methods|July 1, 2018
Improving network inference: The impact of false positive and false negative conclusions about the presence or absence of linksGloria Cecchini, Marco Thiel, Björn Schelter, et al.Journal of Neuroscience Methods|May 12, 2009
Assessing the strength of directed influences among neural signals using renormalized partial directed coherenceBjörn Schelter, Jens Timmer, Michael EichlerJournal of Neuroscience Methods|February 25, 2015
Network inference in the presence of latent confounders: the role of instantaneous causalitiesHeba Elsegai, Helen Shiells, Marco Thiel, et al.Ultrasound in Medicine & Biology|July 6, 2012
Grading of dynamic cerebral autoregulation without blood pressure recordings: a simple Doppler-based methodLinda Sommerlade, Björn Schelter, Jens Timmer, et al.Physical Review. E|March 19, 2021
Impact of local network characteristics on network reconstructionGloria Cecchini, Rok Cestnik, Arkady PikovskyJournal of Neuroscience Methods|August 13, 2013
Block-bootstrapping for noisy dataMalenka Mader, Wolfgang Mader, Linda Sommerlade, et al.Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|July 30, 2011
Statistical validation of event predictors: a comparative study based on the field of seizure predictionHinnerk Feldwisch-Drentrup, Andreas Schulze-Bonhage, Jens Timmer, et al.Physical Review Letters|June 29, 2006
Partial phase synchronization for multivariate synchronizing systemsBjörn Schelter, Matthias Winterhalder, Rainer Dahlhaus, et al.Scientific Reports|June 5, 2015
Networks: On the relation of bi- and multivariate measuresWolfgang Mader, Malenka Mader, Jens Timmer, et al.Pageof 6