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- J. von Rohrscheidt and B. Rieck: [*Diss-L-Ect: Dissecting Graph Data With Local Euler Characteristic Transforms*](https://arxiv.org/abs/2410.02622), Preprint, 2024<br />
Learning with Missing Values (ARTEMISS)</small>
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## 2025
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###2025
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- L. Hetzel<sup>†</sup>, J. Sommer<sup>†</sup>, B. Rieck, F. Theis, and S. Günnemann: [*MAGNet: Motif-Agnostic Generation of Molecules From Shapes*](https://arxiv.org/abs/2305.19303), International Conference on Learning Representations, 2025 (in press)<br />
- Y. Zhang, L. Mezrag, X. Sun, C. Xu, K. Macdonald, D. Bhaskar, S. Krishnaswamy<sup>‡</sup>, G. Wolf<sup>‡</sup>, and B. Rieck<sup>‡</sup>: [*Principal Curvatures Estimation With Applications to Single Cell Data*](https://arxiv.org/abs/2502.03750), IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025 (in press)<br />
- R. Ballester<sup>†</sup>, E. Röell<sup>†</sup>, D. Bin Schmid<sup>†</sup>, M. Alain<sup>†</sup>, S. Escalera, C. Casacuberta, and B. Rieck: [*MANTRA: The Manifold Triangulations Assemblage*](https://arxiv.org/abs/2410.02392), International Conference on Learning Representations, 2024 (in press)<br />
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- E. Röell and B. Rieck: [*Differentiable Euler Characteristic Transforms for Shape Classification*](https://openreview.net/forum?id=MO632iPq3I), International Conference on Learning Representations, 2024<br />
- C. Morris, Y. Lipman, H. Maron, B. Rieck, N. M. Kriege, M. Grohe, M. Fey, and K. Borgwardt: [*Weisfeiler and Leman Go Machine Learning: The Story So Far*](https://arxiv.org/abs/2112.09992), Journal of Machine Learning Research, Volume 24, Number 333, pp. 1--59, 2023<br />
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- C. Coupette, S. Dalleiger, and B. Rieck: [*Ollivier--Ricci Curvature for Hypergraphs: A Unified Framework*](https://openreview.net/forum?id=sPCKNl5qDps), International Conference on Learning Representations, 2023<br />
- D. Thomas, S. Demers, S. Krishnaswamy<sup>‡</sup>, and B. Rieck<sup>‡</sup>: [*Topological Jet Tagging*](https://ml4physicalsciences.github.io/2022/files/NeurIPS_ML4PS_2022_176.pdf), 'Machine Learning and the Physical Sciences' Workshop at NeurIPS, 2022<br />
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COVID-19*](https://dx.doi.org/10.1038/s41587-021-01186-x), Nature Biotechnology, Volume 40, Number 5, pp. 681--691, 2022<br />
- M. Kuijs, C. R. Jutzeler, B. Rieck, and S. C. Brüningk: [*Interpretability Aware Model Training to Improve Robustness Against Out-of-Distribution Magnetic Resonance Images in Alzheimer's Disease Classification*](https://arxiv.org/abs/2111.08701), 'Machine Learning for Health (ML4H)' Symposium, 2021<br />
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- A. C. Gumpinger, B. Rieck, D. G. Grimm, I. H. Consortium, and K. Borgwardt: [*Network-Guided Search for Genetic Heterogeneity Between Gene Pairs*](https://dx.doi.org/10.1093/bioinformatics/btaa581), Bioinformatics, Volume 37, Number 1, pp. 57--65, 2021<br />
- B. Rieck, F. Sadlo, and H. Leitte: [*Persistence Concepts for 2D Skeleton Evolution Analysis*](https://dx.doi.org/10.1007/978-3-030-43036-8_9), Topological Methods in Data Analysis and Visualization V, pp. 139--154, 2020<br />
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- S. L. Hyland<sup>†</sup>, M. Faltys<sup>†</sup>, M. Hüser<sup>†</sup>, X. Lyu<sup>†</sup>, T. Gumbsch<sup>†</sup>, C. Esteban, C. Bock, M. Horn, M. Moor, B. Rieck, M. Zimmermann, D. Bodenham, K. Borgwardt<sup>‡</sup>, G. Rätsch<sup>‡</sup>, and T. M. Merz<sup>‡</sup>: [*Early Prediction of Circulatory Failure in the Intensive Care Unit Using Machine Learning*](https://dx.doi.org/10.1038/s41591-020-0789-4), Nature Medicine, Volume 26, Number 3, pp. 364--373, 2020<br />
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- B. Rieck<sup>†</sup>, M. Togninalli<sup>†</sup>, C. Bock<sup>†</sup>, M. Moor, M. Horn, T. Gumbsch, and K. Borgwardt: [*Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology*](https://openreview.net/forum?id=ByxkijC5FQ), International Conference on Learning Representations, 2019<br />
- C. Bock, T. Gumbsch, M. Moor, B. Rieck, D. Roqueiro, and K. Borgwardt: [*Association Mapping in Biomedical Time Series via Statistically Significant Shapelet Mining*](https://dx.doi.org/10.1093/bioinformatics/bty246), Bioinformatics, Volume 34, Number 13, pp. i438--i446, 2018<br />
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- B. Rieck, U. Fugacci, J. Lukasczyk, and H. Leitte: [*Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks*](https://dx.doi.org/10.1109/TVCG.2017.2744321), IEEE Transactions on Visualization and Computer Graphics, Volume 24, Number 1, pp. 822--831, 2018<br />
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- B. Rieck and H. Leitte: [*Agreement Analysis of Quality Measures for Dimensionality Reduction*](https://dx.doi.org/10.1007/978-3-319-44684-4_6), Topological Methods in Data Analysis and Visualization IV, pp. 103--117, 2017<br />
- B. Rieck and H. Leitte: [*'Shall I Compare Thee to a Network?' --- Visualizing the Topological Structure of Shakespeare's Plays*](https://bastian.rieck.me/research/Vis2016.pdf), Workshop on Visualization for the Digital Humanities at IEEE Vis, 2016<br />
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- J. Fangerau, B. Höckendorf, B. Rieck, C. Heine, J. Wittbrodt, and H. Leitte: [*Interactive Similarity Analysis and Error Detection in Large Tree Collections*](https://dx.doi.org/10.1007/978-3-319-24523-2_13), Visualization in Medicine and Life Sciences III, pp. 287--307, 2016<br />
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<small>[\[BibTeX\]](Fangerau16.bib)</small>
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## 2015
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###2015
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- B. Rieck and H. Leitte: [*Comparing Dimensionality Reduction Methods Using Data Descriptor Landscapes*](https://bastian.rieck.me/research/Vis2015.pdf), Symposium on Visualization in Data Science (VDS) at IEEE VIS, 2015<br />
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<small>[\[BibTeX\]](Rieck15c.bib)</small>
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- B. Rieck and H. Leitte: [*Agreement Analysis of Quality Measures for Dimensionality Reduction*](https://bastian.rieck.me/research/TopoInVis2015.pdf), Workshop on Topology-Based Methods in Visualization (TopoInVis), 2015<br />
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<small>[\[BibTeX\]](Rieck15a.bib)</small>
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## 2014
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###2014
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- B. Rieck and H. Leitte: [*Enhancing Comparative Model Analysis Using Persistent Homology*](https://bastian.rieck.me/research/Vis2014.pdf), IEEE Vis Workshop on Visualization for Predictive Analytics, 2014<br />
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<small>[\[BibTeX\]](Rieck14b.bib)</small>
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- B. Rieck and H. Leitte: [*Structural Analysis of Multivariate Point Clouds Using Simplicial Chains*](https://dx.doi.org/10.1111/cgf.12398), Computer Graphics Forum, Volume 33, Number 8, pp. 28--37, 2014<br />
- B. Rieck, H. Mara, and S. Krömker: [*Unwrapping Highly-Detailed 3D Meshes of Rotationally Symmetric Man-Made Objects*](https://dx.doi.org/10.5194/isprsannals-II-5-W1-259-2013), ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume II-5/W1, pp. 259--264, 2013<br />
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<small>[\[BibTeX\]](Rieck13a.bib)</small>
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- M. Forbriger, H. Mara, B. Rieck, C. Siart, and O. Wagener: [*Der “Gesprengte Turm” Am Heidelberger Schloss -- Untersuchung Eines Kulturdenkmals Mithilfe Hoch Auflösender Terrestrischer Laserscans*](https://bastian.rieck.me/research/Gesprengter_Turm.pdf), Denkmalpflege in Baden-Württemberg, Nachrichtenblatt der Landesdenkmalpflege, Volume 3, pp. 165--168, 2013<br />
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<small>[\[BibTeX\]](Forbriger13a.bib)</small>
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## 2012
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###2012
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- B. Rieck, H. Mara, and H. Leitte: [*Multivariate Data Analysis Using Persistence-Based Filtering and Topological Signatures*](https://dx.doi.org/10.1109/TVCG.2012.248), IEEE Transactions on Visualization and Computer Graphics, Volume 18, Number 12, pp. 2382--2391, 2012<br />
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