3 papers
cs.LG2026
A Critical Audit of Spatiotemporal Forecasting Benchmark Datasets and Baselines
Kenneth Martin, Simon Heilig, Asja Fischer +3
Graph neural networks (GNNs) are routinely employed for short-range forecasting on multivariate time series with a spatial graph structure. Despite the availability of many alterna…
cs.LG2025
Towards an Optimal Control Perspective of ResNet Training
Jens Püttschneider, Simon Heilig, Asja Fischer +1
We propose a training formulation for ResNets reflecting an optimal control problem that is applicable for standard architectures and general loss functions. We suggest bridging bo…
cs.LG2025
Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
Simon Heilig, Alessio Gravina, Alessandro Trenta +2
The dynamics of information diffusion within graphs is a critical open issue that heavily influences graph representation learning, especially when considering long-range propagati…