
PhD Student
MC 5.127
simon.heilig@rub.de
Personal Website
→ ELLIS PhD Student
Research Interests
- machine learning for spatiotemporal data
- theory and application of graph neural networks
- graph-coupled neural ODEs
Publications
2025
Simon Heilig, Alessio Gravina, Alessandro Trenta, Claudio Gallicchio, Davide Bacciu
Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks Proceedings Article
In: International Conference on Learning Representations (ICLR), 2025.
@inproceedings{Heilig2025Port-HamiltonianArchitectural,
title = {Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks},
author = {Simon Heilig and Alessio Gravina and Alessandro Trenta and Claudio Gallicchio and Davide Bacciu},
url = {https://openreview.net/forum?id=03EkqSCKuO},
year = {2025},
date = {2025-01-01},
booktitle = {International Conference on Learning Representations (ICLR)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2023
Maximilian Münch, Manuel Röder, Simon Heilig, Christoph Raab, Frank-Michael Schleif
Static and Adaptive Subspace Information Fusion for Indefinite Heterogeneous Proximity Data Artikel
In: Neurocomputing, 2023.
@article{Münch2023Staticand,
title = {Static and Adaptive Subspace Information Fusion for Indefinite Heterogeneous Proximity Data},
author = {Maximilian Münch and Manuel Röder and Simon Heilig and Christoph Raab and Frank-Michael Schleif},
url = {https://doi.org/10.1016/j.neucom.2023.126635},
year = {2023},
date = {2023-01-01},
journal = {Neurocomputing},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2022
Simon Heilig, Maximilian Münch, Frank-Michael Schleif
Memory Efficient Kernel Approximation for Non-Stationary and Indefinite Kernels Proceedings Article
In: International Joint Conference on Neural Networks (IJCNN), 2022.
@inproceedings{Heilig2022MemoryEfficient,
title = {Memory Efficient Kernel Approximation for Non-Stationary and Indefinite Kernels},
author = {Simon Heilig and Maximilian Münch and Frank-Michael Schleif},
url = {https://doi.org/10.1109/IJCNN55064.2022.9892153},
year = {2022},
date = {2022-01-01},
booktitle = {International Joint Conference on Neural Networks (IJCNN)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}