The paper "Predicting Influential Higher-Order Patterns in Temporal Network Data" has received the Best Student Paper award.
Congratulations from CAIDAS to Christoph Gote, Vincenzo Perri and Ingo Scholtes from the ML4NETS group for their outstanding contribution to The 2022 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining.
paper: "Predicting Influential Higher-Order Patterns in Temporal Network Data"
By clicking 'OK' you are leaving the web sites of the Julius-Maximilians-Universität Würzburg and will be redirected to Facebook. For information on the collection and processing of data by Facebook, refer to the social network's data privacy statement.
By clicking 'OK' you are leaving the web sites of the Julius-Maximilians-Universität Würzburg and will be redirected to Twitter. For information on the collection and processing of data by Facebook, refer to the social network's data privacy statement.
