33 citations · 53 across the 5 of their papers we have counts for
5 papers
Unifying Physics- and Data-Driven Modeling via Novel Causal Spatiotemporal Graph Neural Network for Interpretable Epidemic Forecasting
Shuai Han, Lukas Stelz, Thomas R. Sokolowski +2
Accurate epidemic forecasting is crucial for effective disease control and prevention. Traditional compartmental models often struggle to estimate temporally and spatially varying…
Learning COVID-19 Regional Transmission Using Universal Differential Equations in a SIR model
Adrian Rojas-Campos, Lukas Stelz, Pascal Nieters
Highly-interconnected societies difficult to model the spread of infectious diseases such as COVID-19. Single-region SIR models fail to account for incoming forces of infection and…
Approaching epidemiological dynamics of COVID-19 with physics-informed neural networks
Shuai Han, Lukas Stelz, Horst Stoecker +2
A physics-informed neural network (PINN) embedded with the susceptible-infected-removed (SIR) model is devised to understand the temporal evolution dynamics of infectious diseases.…
Charting closed-loop collective cultural decisions: From book best sellers and music downloads to Twitter hashtags and Reddit comments
Lukas Schneider, Johannes Scholten, Bulcsu Sandor +1
Charts are used to measure relative success for a large variety of cultural items. Traditional music charts have been shown to follow self-organizing principles with regard to the…
Five decades of US, UK, German and Dutch music charts show that cultural processes are accelerating
Lukas Schneider, Claudius Gros
Analyzing the timeline of US, UK, German and Dutch music charts, we find that the evolution of album lifetimes and of the size of weekly rank changes provide evidence for an accele…