activity
20162022
most citedWhy We Read Wikipedia

90 citations · 108 across the 10 of their papers we have counts for

collaborators

20 papers

cs.LG2022

On the Prediction Instability of Graph Neural Networks

Max Klabunde, Florian Lemmerich

Instability of trained models, i.e., the dependence of individual node predictions on random factors, can affect reproducibility, reliability, and trust in machine learning systems…

cs.LG20213 cited

Updating Embeddings for Dynamic Knowledge Graphs

Christopher Wewer, Florian Lemmerich, Michael Cochez

Data in Knowledge Graphs often represents part of the current state of the real world. Thus, to stay up-to-date the graph data needs to be updated frequently. To utilize informatio…

cs.DB20211 cited

Redescription Model Mining

Felix I. Stamm, Martin Becker, Markus Strohmaier +1

This paper introduces Redescription Model Mining, a novel approach to identify interpretable patterns across two datasets that share only a subset of attributes and have no common…

cs.LG2021

Surfacing Estimation Uncertainty in the Decay Parameters of Hawkes Processes with Exponential Kernels

Tiago Santos, Florian Lemmerich, Denis Helic

As a tool for capturing irregular temporal dependencies (rather than resorting to binning temporal observations to construct time series), Hawkes processes with exponential decay h…

cs.CY2021

The FairCeptron: A Framework for Measuring Human Perceptions of Algorithmic Fairness

Georg Ahnert, Ivan Smirnov, Florian Lemmerich +2

Measures of algorithmic fairness often do not account for human perceptions of fairness that can substantially vary between different sociodemographics and stakeholders. The FairCe…

cs.CY2021

Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictions

Thorsten Ruprechter, Manoel Horta Ribeiro, Tiago Santos +4

Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions. When the COVID-19 pandemic broke out and mobility restrictions ensued ac…