A full publication list can be found on Google Scholar.
Publicly available code repositories can be found on our group GitHub.
Selected Works
B Tahmasebi, M Weber. Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry Preliminary version in Tag-DS 2025 (Oral presentation).
W Diepeveen, M Weber. Iso-Riemannian Optimization on Learned Data Manifolds arXiv:2510.21033
M Hehl, M-K von Renesse, M Weber. Neural Feature Geometry Evolves as Discrete Ricci Flow arXiv:2509.22362
R Pellegrin*, L Fesser*, M Weber. Enhancing the Utility of Higher-Order Information in Relational Learning NeurIPS 2025
N Bhasker, H Chung, L Boucherie, V Kim, S Speidel, M Weber. Uncovering Developmental Lineages from Single-cell Data with Contrastive Poincaré Maps bioRxiv: 10.1101/2025.08.22.671789
J Wang, L Fesser, M Weber. Balancing Fairness and Accuracy in Graph Learning via Fairness-Constrained Rewiring Symmetry and Geometry in Neural Representations 2025 🏆 Best Paper Award
A Lee, M Weber, F Viégas, M Wattenberg. Shared Global and Local Geometry of Language Model Embeddings Conference on Language Modeling 2025 🏆 Outstanding Paper Award
N He, J Liu, B Zhang, M Bui, A Maatouk, M Yang, I King, M Weber, R Ying. Beyond Euclidean – Foundation Models Should Embrace Non-Euclidean Geometries. Learning on Graphs 2025 🏆 Oral presentation
Z Shumaylov*, P Zaika*, J Rowbottom, F Sherry, M Weber, and CB Schönlieb. Lie algebra canonicalization: Equivariant neural operators under
arbitrary Lie groups ICLR 2025
Y Tian*, Z Lubberts*, M Weber. Curvature-based Clustering on Graphs Journal of Machine Learning Research 2025
M Weber. Geometric Machine Learning. AI Magazine 2025
A Cheng, M Weber. Structured Regularization for Constrained Optimization on the SPD Manifold Allerton Conference on Communication, Control, and Computing 2024
B Kiani, L Fesser, M Weber. Unitary Convolutions for Learning on Graphs and Groups NeurIPS 2024 🏆 Spotlight
A Cheng, V Dixit, M Weber. Disciplined Geodesically Convex Programming arXiv:2407.05261
A Feng, M Weber. Graph Pooling via Ricci Flow Transactions on Machine Learning Research 2024
B Kiani, J Wang, M Weber. Hardness of Learning Neural Networks under the Manifold Hypothesis NeurIPS 2024 🏆 Spotlight
B Kiani*, T Le*, H Lawrence*, S Jegelka, M Weber. On the Hardness of Learning under Symmetries ICLR 2024 🏆 Spotlight
L Fesser, M Weber. Effective Structural Encodings via Local Curvature Profiles ICLR 2024
L Fesser, M Weber. Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature Learning on Graphs 2023
N Garcia Trillos, M Weber. Continuum Limits of Ollivier’s Ricci Curvature on data clouds: pointwise consistency and global lower bounds Under Review (2023). arXiv:2307.02378
M Weber, S Sra. Global optimality for Euclidean CCCP under Riemannian convexity ICML 2023
M Weber, S Sra. Riemannian Optimization via Frank-Wolfe Methods Mathematical Programming 2022
M Weber, S Sra. Projection-free nonconvex stochastic optimization on Riemannian manifolds IMA Numerical Analysis 2021
M Weber, M Zaheer, AS Rawat, A Menon, S Kumar. Robust Large-Margin Learning in Hyperbolic Space NeurIPS 2020
M Weber. Neighborhood Growth Determines Geometric Priors for Relational Representation Learning AISTATS 2020
M Weber, E Saucan, J Jost. Coarse Geometry of Evolving Networks Journal of Complex Networks 2018
M Weber, E Saucan, J Jost. Characterizing Complex Networks with Forman-Ricci Curvature and Associated Geometric Flows Journal of Complex Networks 2017