4 papers
Can Graph Learning Learn Circuits?
Chester Tan, Moritz Lampert, Courtney Maynard +3
Circuit localization is a mechanistic interpretability task whose goal is to identify a sparse subgraph of a transformer's computation graph sufficient to reproduce a particular be…
Single-Snapshot Inference of Network Couplings from Universal Dynamics at Relative Equilibrium
Moritz Lampert, Dominic Grün, Ingo Scholtes
Many real-world systems can be modelled as complex networks whose collective behaviour is governed by hidden interactions between nodes. Existing methods for inferring these intera…
From Link Prediction to Forecasting: Addressing Challenges in Batch-based Temporal Graph Learning
Moritz Lampert, Christopher Blöcker, Ingo Scholtes
Dynamic link prediction is an important problem considered in many recent works that propose approaches for learning temporal edge patterns. To assess their efficacy, models are ev…
The Self-Loop Paradox: Investigating the Impact of Self-Loops on Graph Neural Networks
Moritz Lampert, Ingo Scholtes
Many Graph Neural Networks (GNNs) add self-loops to a graph to include feature information about a node itself at each layer. However, if the GNN consists of more than one layer, t…