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cs.LG2022★ 1 cited
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs
Lisi Qarkaxhija, Vincenzo Perri, Ingo Scholtes
We introduce De Bruijn Graph Neural Networks (DBGNNs), a novel time-aware graph neural network architecture for time-resolved data on dynamic graphs. Our approach accounts for temp…
cs.LG2020★ 2 cited
Learning the Markov order of paths in a network
Luka V. Petrović, Ingo Scholtes
We study the problem of learning the Markov order in categorical sequences that represent paths in a network, i.e. sequences of variable lengths where transitions between states ar…