4 papers
A Counting Process View of Relational Event Models: Practical Asymptotics
Cornelius Fritz, Alexander Fuchs-Kreiss
Relational Event Models (REMs) provide a rigorous framework for analyzing dyadic interactions observed in continuous time, capturing history-dependent dynamics such as triadic clos…
Scalable Durational Event Models: Application to Physical and Digital Interactions
Cornelius Fritz, Riccardo Rastelli, Michael Fop +1
Durable interactions are ubiquitous in social network analysis and are increasingly observed with precise time stamps. Phone and video calls, for example, are events to which a spe…
Scalable Signed Exponential Random Graph Models under Local Dependence
Marc Schalberger, Cornelius Fritz
Traditional network analysis focuses on binary edges, while real-world relationships are more nuanced, encompassing cooperation, neutrality, and conflict. The rise of negative edge…
How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression
Lucas Kook, Chris Kolb, Philipp Schiele +8
Neural network representations of simple models, such as linear regression, are being studied increasingly to better understand the underlying principles of deep learning algorithm…