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Preprint
- Hoppe, J., Grande, V. P., & Schaub, M. T. (2025). Don’t be Afraid of Cell Complexes! An Introduction from an Applied Perspective (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2506.09726
Josef Hoppe, Vincent P. Grande, Michael T. Schaub
- Patel, D., Savostianov, A., & Schaub, M. T. (2025). Convergence of gradient based training for linear Graph Neural Networks (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2501.14440
Dhiraj Patel, Anton Savostianov, Michael T. Schaub
- Savostianov, A., Schaub, M. T., & Stamm, B. (2025). Grassmanian Interpolation of Low-Pass Graph Filters: Theory and Applications (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2510.23235
Anton Savostianov, Michael T. Schaub, Benjamin Stamm
- Savostianov, A., Schaub, M. T., Guglielmi, N., & Tudisco, F. (2025). Efficient Sparsification of Simplicial Complexes via Local Densities of States (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2502.07558
Anton Savostianov, Michael T. Schaub, Nicola Guglielmi, Francesco Tudisco
- Hoppe, J., & Schaub, M. T. (2024). Random Abstract Cell Complexes (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2406.01999
Josef Hoppe, Michael T. Schaub
- Telyatnikov, L., Bernardez, G., Montagna, M., Hajij, M., Carrasco, M., Vasylenko, P., Papillon, M., Zamzmi, G., Schaub, M. T., Verhellen, J., Snopov, P., Miquel-Oliver, B., Gil-Sorribes, M., Molina, A., Guallar, V., Long, T., Suk, J., Rygiel, P., Nikitin, A., … Papamarkou, T. (2024). TopoBench: A Framework for Benchmarking Topological Deep Learning (Version 3). arXiv. https://doi.org/10.48550/ARXIV.2406.06642
Lev Telyatnikov, Guillermo Bernardez, Marco Montagna, Mustafa Hajij, Martin Carrasco, Pavlo Vasylenko, Mathilde Papillon, Ghada Zamzmi, Michael T. Schaub, Jonas Verhellen, Pavel Snopov, Bertran Miquel-Oliver, Manel Gil-Sorribes, Alexis Molina, Victor Guallar, Theodore Long, Julian Suk, Patryk Rygiel, Alexander Nikitin, Giordan Escalona, Michael Banf, Dominik Filipiak, Max Schattauer, Liliya Imasheva, Alvaro Martinez, Halley Fritze, Marissa Masden, Valentina Sánchez, Manuel Lecha, Andrea Cavallo, Claudio Battiloro, Matt Piekenbrock, Mauricio Tec, George Dasoulas, Nina Miolane, Simone Scardapane, Theodore Papamarkou
- Hajij, M., Zamzmi, G., Papamarkou, T., Miolane, N., Guzmán-Sáenz, A., Ramamurthy, K. N., Birdal, T., Dey, T. K., Mukherjee, S., Samaga, S. N., Livesay, N., Walters, R., Rosen, P., & Schaub, M. T. (2022). Topological Deep Learning: Going Beyond Graph Data (Version 3). arXiv. https://doi.org/10.48550/ARXIV.2206.00606
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Nina Miolane, Aldo Guzmán-Sáenz, Karthikeyan Natesan Ramamurthy, Tolga Birdal, Tamal K. Dey, Soham Mukherjee, Shreyas N. Samaga, Neal Livesay, Robin Walters, Paul Rosen, Michael T. Schaub
2025
- Spreuer, T., Hoppe, J., & Schaub, M. T. (2025). Faster Inference of Cell Complexes from Flows via Matrix Factorization. 2025 33rd European Signal Processing Conference (EUSIPCO), 2487–2491. https://doi.org/10.23919/eusipco63237.2025.11226659
Til Spreuer, Josef Hoppe, Michael T. Schaub
- Frantzen, F., & Schaub, M. T. (2025). HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2, 626–636. https://doi.org/10.1145/3711896.3736998
Florian Frantzen, Michael T. Schaub
- Grande, V. P., & Schaub, M. T. (2025). Point-Level Topological Representation Learning on Point Clouds. In A. Singh, M. Fazel, D. Hsu, S. Lacoste-Julien, F. Berkenkamp, T. Maharaj, K. Wagstaff, & J. Zhu (Eds.), Proceedings of the 42th International Conference on Machine Learning (Vol. 267, pp. 20368–20398). PMLR.
Vincent P Grande, Michael T Schaub
- Kühn, D., & Schaub, M. T. (2025). Global Ground Metric Learning with Applications to scRNA Data. Proceedings of the 28th International Conference on Artificial Intelligence and Statistics, 258, 3295–3303. https://proceedings.mlr.press/v258/kuhn25a.html
Damin Kühn, Michael T. Schaub
- Rompelberg, L., & Schaub, M. T. (2025). A Bayesian Perspective on Uncertainty Quantification for Estimated Graph Signals. ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1–5. https://doi.org/10.1109/icassp49660.2025.10889783
Lennard Rompelberg, Michael T. Schaub
- René, A., & Longtin, A. (2025). Selecting fitted models under epistemic uncertainty using a stochastic process on quantile functions. Nature Communications, 16(1). https://doi.org/10.1038/s41467-025-64658-7
Alexandre René, André Longtin
- Cheng, M., Jansen, J., Reimer, K. C., Grande, V. P., Nagai, J. S., Li, Z., Kießling, P., Grasshoff, M., Kuppe, C., Schaub, M. T., Kramann, R., & Costa, I. G. (2025). PHLOWER leverages single-cell multimodal data to infer complex, multi-branching cell differentiation trajectories. Nature Methods, 22(11), 2328–2336. https://doi.org/10.1038/s41592-025-02870-5
Mingbo Cheng, Jitske Jansen, Katharina C. Reimer, Vincent P. Grande, James S. Nagai, Zhijian Li, Paul Kießling, Martin Grasshoff, Christoph Kuppe, Michael T. Schaub, Rafael Kramann, Ivan G. Costa
2024
- Papamarkou, T., Birdal, T., Bronstein, M. M., Carlsson, G. E., Curry, J., Gao, Y., Hajij, M., Kwitt, R., Lio, P., Di Lorenzo, P., Maroulas, V., Miolane, N., Nasrin, F., Natesan Ramamurthy, K., Rieck, B., Scardapane, S., Schaub, M. T., Veličković, P., Wang, B., … Zamzmi, G. (2024). Position: Topological Deep Learning is the New Frontier for Relational Learning. In R. Salakhutdinov, Z. Kolter, K. Heller, A. Weller, N. Oliver, J. Scarlett, & F. Berkenkamp (Eds.), Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 39529–39555). PMLR. https://proceedings.mlr.press/v235/papamarkou24a.html
Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T Schaub, Petar Veličković, Bei Wang, Yusu Wang, Guowei Wei, Ghada Zamzmi
- Neuhäuser, L., Scholkemper, M., Tudisco, F., & Schaub, M. T. (2024). Learning the effective order of a hypergraph dynamical system. Science Advances, 10(19). https://doi.org/10.1126/sciadv.adh4053
Leonie Neuhäuser, Michael Scholkemper, Francesco Tudisco, Michael T. Schaub
- Scholkemper, M., Kühn, D., Nabbefeld, G., Musall, S., Kampa, B., & Schaub, M. T. (2024). A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 9751–9755. https://doi.org/10.1109/icassp48485.2024.10447922
Michael Scholkemper, Damin Kühn, Gerion Nabbefeld, Simon Musall, Björn Kampa, Michael T. Schaub
- Grande, V. P., & Schaub, M. T. (2024). Disentangling the Spectral Properties of the Hodge Laplacian: not all small Eigenvalues are Equal. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 9896–9900. https://doi.org/10.1109/icassp48485.2024.10446051
Vincent P. Grande, Michael T. Schaub
- Hoppe, J., & Schaub, M. T. (2024). Representing Edge Flows on Graphs via Sparse Cell Complexes. In S. Villar & B. Chamberlain (Eds.), Proceedings of the Second Learning on Graphs Conference (Vol. 231, p. 1:1-1:22). PMLR. https://proceedings.mlr.press/v231/hoppe24a.html
Josef Hoppe, Michael T Schaub
- Grande, V. P., & Schaub, M. T. (2024). Non-Isotropic Persistent Homology: Leveraging the Metric Dependency of PH. In S. Villar & B. Chamberlain (Eds.), Proceedings of the Second Learning on Graphs Conference (Vol. 231, p. 17:1-17:19). PMLR. https://proceedings.mlr.press/v231/grande24a.html
Vincent Peter Grande, Michael T Schaub
- Savostianov, A., Tudisco, F., & Guglielmi, N. (2024). Cholesky-like Preconditioner for Hodge Laplacians via Heavy Collapsible Subcomplex. SIAM Journal on Matrix Analysis and Applications, 45(4), 1827–1849. https://doi.org/10.1137/23m1626396
Anton Savostianov, Francesco Tudisco, Nicola Guglielmi
- Grande, V. P., Hoppe, J., Frantzen, F., & Schaub, M. T. (2024). Topological Trajectory Classification and Landmark Inference on Simplicial Complexes. 2024 58th Asilomar Conference on Signals, Systems, and Computers, 44–48. https://doi.org/10.1109/ieeeconf60004.2024.10942887
Vincent P. Grande, Josef Hoppe, Florian Frantzen, Michael T. Schaub
- Epping, B., René, A., Helias, M., & Schaub, M. T. (2024). Graph Neural Networks Do Not Always Oversmooth. In A. Globerson, L. Mackey, D. Belgrave, A. Fan, U. Paquet, J. Tomczak, & C. Zhang (Eds.), Advances in Neural Information Processing Systems (Vol. 37, pp. 48164–48188). Curran Associates, Inc.
Bastian Epping, Alexandre René, Moritz Helias, Michael T. Schaub
- Frantzen, F., & Schaub, M. T. (2024). Learning From Simplicial Data Based on Random Walks and 1D Convolutions. The Twelfth International Conference on Learning Representations.
Florian Frantzen, Michael T. Schaub
- Hajij, M., Papillon, M., Frantzen, F., Agerberg, J., AlJabea, I., Ballester, R., Battiloro, C., Bernárdez, G., Birdal, T., Brent, A., Chin, P., Escalera, S., Fiorellino, S., Gardaa, O. H., Gopalakrishnan, G., Govil, D., Hoppe, J., Karri, M. R., Khouja, J., … Miolane, N. (2024). TopoX: A Suite of Python Packages for Machine Learning on Topological Domains. Journal of Machine Learning Research, 25(374), 1–8. http://jmlr.org/papers/v25/24-0110.html
Mustafa Hajij, Mathilde Papillon, Florian Frantzen, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee, Alexander Nikitin, Theodore Papamarkou, Jaro Prílepok, Karthikeyan Natesan Ramamurthy, Paul Rosen, Aldo Guzmán-Sáenz, Alessandro Salatiello, Shreyas N. Samaga, Simone Scardapane, Michael T. Schaub, Luca Scofano, Indro Spinelli, Lev Telyatnikov, Quang Truong, Robin Walters, Maosheng Yang, Olga Zaghen, Ghada Zamzmi, Ali Zia, Nina Miolane
2023
- Grande, V. P., & Schaub, M. T. (2023). Topological Point Cloud Clustering. In A. Krause, E. Brunskill, K. Cho, B. Engelhardt, S. Sabato, & J. Scarlett (Eds.), Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 11683–11697). PMLR. https://proceedings.mlr.press/v202/grande23a.html
Vincent Peter Grande, Michael T Schaub
- Roddenberry, T. M., Grande, V. P., Frantzen, F., Schaub, M. T., & Segarra, S. (2023). Signal Processing On Product Spaces. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1–5. https://doi.org/10.1109/icassp49357.2023.10095735
T. Mitchell Roddenberry, Vincent P. Grande, Florian Frantzen, Michael T. Schaub, Santiago Segarra
- Hajij, M., Zamzmi, G., Papamarkou, T., Guzman-Saenz, Ai., Birdal, T., & Schaub, M. T. (2023). Combinatorial Complexes: Bridging the Gap Between Cell Complexes and Hypergraphs. 2023 57th Asilomar Conference on Signals, Systems, and Computers, 799–803. https://doi.org/10.1109/ieeeconf59524.2023.10477018
Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, AIdo Guzman-Saenz, ToIga Birdal, Michael T. Schaub
2022
- Roddenberry, T. M., Frantzen, F., Schaub, M. T., & Segarra, S. (2022). Hodgelets: Localized Spectral Representations of Flows On Simplicial Complexes. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 5922–5926. https://doi.org/10.1109/icassp43922.2022.9747203
T. Mitchell Roddenberry, Florian Frantzen, Michael T. Schaub, Santiago Segarra
- Schaub, M. T., Seby, J.-B., Frantzen, F., Roddenberry, T. M., Zhu, Y., & Segarra, S. (2022). Signal Processing on Simplicial Complexes. In Understanding Complex Systems (pp. 301–328). Springer International Publishing. https://doi.org/10.1007/978-3-030-91374-8_12
Michael T. Schaub, Jean-Baptiste Seby, Florian Frantzen, T. Mitchell Roddenberry, Yu Zhu, Santiago Segarra
2021
- Frantzen, F., Seby, J.-B., & Schaub, M. T. (2021). Outlier Detection for Trajectories via Flow-embeddings. 2021 55th Asilomar Conference on Signals, Systems, and Computers, 1568–1572. https://doi.org/10.1109/ieeeconf53345.2021.9723128
Florian Frantzen, Jean-Baptiste Seby, Michael T. Schaub