Publications

Equal contribution is marked with a $^{\dagger}$, and equal supervision is marked with a $^{\ast}$.

Preprints

networkGWAS: A network-based approach for genome-wide association studies in structured populations
Giulia Muzio, Leslie O’Bray, Laetitia Meng-Papaxanthos, Juliane Klatt and Karsten Borgwardt
Preprint, 2021.
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The magnitude vector of images
Michael Adamer, Leslie O’Bray, Edward De Brouwer, Bastian Rieck$^{\ast}$, Karsten Borgwardt$^{\ast}$
Preprint, 2021.
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2022

Structure-Aware Transformer for Graph Representation Learning
Dexiong Chen$^{\dagger}$, Leslie O’Bray$^{\dagger}$, Karsten Borgwardt
Accepted for short presentation at the International Conference on Machine Learning (ICML), 2022.
Bibtex

Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
Leslie O’Bray$^{\dagger}$, Max Horn$^{\dagger}$, Bastian Rieck$^{\ast}$ and Karsten Borgwardt$^{\ast}$
Accepted as a Spotlight paper at the International Conference on Learning Representations (ICLR), 2022.
Bibtex

2021

Filtration Curves for Graph Representation
Leslie O’Bray$^{\dagger}$, Bastian Rieck$^{\dagger}$ and Karsten Borgwardt
Accepted for Presentation at KDD, 2021.
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Advances in Graph Kernels.
Kazu Ghalamkari, Mahito Sugiyama, Leslie O’Bray, Bastian Rieck, and Karsten Borgwardt.
Journal of the Japanese Society for Artificial Intelligence 36:4, pp. 421–429, 2021.
This is an abridged translation of our review article ‘Graph Kernels: State-of-the-Art and Future Challenges.’
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2020

Biological Network Analysis with Deep Learning
Giulia Muzio$^{\dagger}$, Leslie O’Bray$^{\dagger}$ and Karsten Borgwardt
Briefings in Bioinformatics, 2020.
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Graph Kernels: State-of-the-Art and Future Challenges
Karsten Borgwardt, Elisabetta Ghisu, Felipe Llinares-López, Leslie O’Bray and Bastian Rieck
Foundations and Trends in Machine Learning, 2020.
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