Publications

E. Singh Lubana*, C. Rager*, S. S. R. Hindupur*, V. Costa, G. Tuckute, O. Patel, S. Krishna Murthy, T. Fel, D. Wurgaft, E. J. Bigelow, J. Lin, D. Ba, M. Wattenberg, F. Viégas, M. Weber, A. Mueller (2026). Priors in Time: Missing Inductive Biases for Language Model Interpretability. ICLR.

Preprint PDF Project

B. Choi, M. Weber (2026). Latent Structure of Affective Representations in Large Language Models. arXiv.

Preprint PDF Project

B. Tahmasebi, M. Weber (2026). Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry. ICLR.

Preprint PDF Project

L. Fesser, B. T. Kiani, M. Weber (2026). Unitary Convolutions for Message-passing and Positional Encodings on Directed Graphs. ICML.

Preprint Project

A. Cheng*, M. Weber (2026). Structured Regularization for Constrained Optimization on the SPD Manifold. IMA Journal of Numerical Analysis.

Preprint Project

J. Krook*, A. Janson*, J. Andén, M. Weber, O. Öktem (2026). Protein Graph Neural Networks for Heterogeneous Cryo-EM Reconstruction. ICIP.

Preprint PDF Project

M. Hehl, M.-K. von Renesse, M. Weber (2026). Neural Feature Geometry Evolves as Discrete Ricci Flow. ICML (spotlight).

K. Vanderbush, M. Weber (2026). Neural Algorithmic Reasoning for Approximate k-Coloring with Recursive Warm Starts. MLST.

Preprint PDF Project

A. Cheng*, V. Dixit*, M. Weber (2026). Disciplined Geodesically Convex Programming: A Symbolic Framework for Verifying Geodesic Convexity. Math. Program. Comput..

Preprint Project

B. Tahmasebi, M. Weber, S. Jegelka (2026). Data Augmentation: A Fourier Analysis Perspective. COLT.

Preprint Project

N. García Trillos, M. Weber (2026). Continuum Limits of Ollivier’s Ricci Curvature on data clouds: pointwise consistency and global lower bounds. Discrete Comput. Geom..

B. Tahmasebi, M. Weber (2026). Adaptive Symmetry Discovery for Dynamical System Identification. ICML.

Preprint Project

T. Le, M. Weber (2025). Towards distillation guarantees under algorithmic alignment for combinatorial optimization. NeurIPS DLA Workshop.

Preprint PDF Project

R. Pellegrin*, L. Fesser, M. Weber (2025). Higher-Order Learning with Graph Neural Networks via Hypergraph Encodings. NeurIPS.

PDF Code Project

J. Wang, L. Fesser, M. Weber (2025). Balancing Fairness and Accuracy in Graph Learning via Fairness-Constrained Rewiring. NeurIPS SGN Workshop (Best Paper Award).

Preprint Project

N. He, J. Liu, B. Zhang, M. Bui, A. Maatouk, M. Yang, I. King, M. Weber, R. Ying (2025). Beyond Euclidean - Foundation Models Should Embrace Non-Euclidean Geometries. LoG (oral).

A. Lee, M. Weber, F. Viégas, M. Wattenberg (2025). Shared Global and Local Geometry of Language Model Embeddings. COLM (Outstanding Paper Award).

W. Diepeveen, M. Weber (2025). Iso-Riemannian Optimization on Learned Data Manifolds. arXiv.

Preprint PDF Project

N. Bhasker, H. Chung, L. Boucherie, V. Kim, S. Speidel, M. Weber (2025). Uncovering Developmental Lineages from Single-cell Data with Contrastive Poincaré Maps. bioRxiv.

Preprint PDF Project

Z. Shumaylov*, P. Zaika*, J. Rowbottom, F. Sherry, M. Weber, C.-B. Schönlieb (2025). Lie algebra canonicalization: Equivariant neural operators under arbitrary Lie groups. ICLR.

Y. Tian, Z. Lubberts, M. Weber (2025). Curvature-based Clustering on Graphs. JMLR.

L. Fesser, M. Weber (2025). Performance Heterogeneity in Graph Neural Networks: Lessons for Architecture Design and Preprocessing. Under Review.

M. Weber (2025). Geometric Machine Learning. AI Magazine.

A. Cheng*, M. Weber (2024). Structured Regularization for SPD Optimization with Side Information. Allerton.

B. T. Kiani, L. Fesser, M. Weber (2024). Unitary convolutions for learning on graphs and groups. NeurIPS (spotlight).

A. Feng, M. Weber (2024). Graph Pooling via Ricci Flow. TMLR.

B. T. Kiani, J. Wang, M. Weber (2024). Hardness of Learning Neural Networks under the Manifold Hypothesis. NeurIPS (spotlight).

B. T. Kiani, T. Le, H. Lawrence, S. Jegelka, M. Weber (2024). On the Hardness of Learning under Symmetries. ICLR (spotlight).

L. Fesser, M. Weber (2024). Effective Structural Encodings via Local Curvature Profiles. ICLR.

L. Fesser, M. Weber (2023). Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature. Learning on Graphs.

M. Weber, P. Bachman (2023). Sampling Informative Positives Pairs in Contrastive Learning. SampTA.

L. Fesser, S. Serrano de Haro Iváñez, K. Devriendt, M. Weber, R. Lambiotte (2023). Augmentations of Forman's Ricci Curvature and their Applications in Community Detection. J. Physics: Complexity.

M. Weber, S. Sra (2023). Global optimality for Euclidean CCCP under Riemannian convexity. ICML.

Preprint Project

W. Hua, Y. Zhang, Z. Chen, J. Li, M. Weber (2022). LegalRelectra: Mixed-domain Language Modeling for Long-range Legal Text Comprehension. NLLP.

J. Carruth, M. F. Eggl, C. Fefferman, C. W. Rowley, M. Weber (2022). Controlling Unknown Linear Dynamics with Bounded Multiplicative Regret. Rev. Mat. Iberoamericana.

Preprint PDF Project

Y. Tian, Z. Lubberts, M. Weber (2022). Mixed-Membership Community Detection via Line Graph Curvature. Symmetry and Geometry in Neural Representations.

M. Weber, S. Sra (2022). Computing Brascamp-Lieb Constants through the lens of Thompson Geometry. Under Review.

Preprint Project

M. Weber, S. Sra (2022). Riemannian Optimization via Frank-Wolfe Methods. Mathematical Programming.

PDF Code Project Video

J. Sargent, M. Weber (2021). Identifying biases in legal data: An algorithmic fairness perspective. ACM EAAMO.

M. Weber, S. Sra (2021). Projection-free nonconvex stochastic optimization on Riemannian manifolds. IMA Journal of Numerical Analysis.

Preprint PDF Project

C. Fefferman, B. Guillen Pegueroles, C. W. Rowley, M. Weber (2021). Optimal control with learning on the fly. Rev. Mat. Iberoamericana.

Preprint PDF Project

M. Weber (2021). On Geometric Optimization, Learning and Control. PhD Thesis, Princeton University.

M. Weber, M. Zaheer, A. Singh Rawat, A. Menon, S. Kumar (2020). Robust Large-Margin Learning in Hyperbolic Space. NeurIPS.

Preprint PDF Project Video

E. E. Groth, M. Weber, T. Bahmer, F. Pedersen, A. Kirsten, D. Börnigen, K. F. Rabe, H. Watz, O. Ammerpohl, T. Goldmann (2020). Exploration of the sputum methylome and omics deconvolution by quadratic programming in molecular profiling of asthma and COPD: the road to sputum omics 2.0. Respiratory Research.

M. Weber (2020). Neighborhood Growth Determines Geometric Priors for Relational Representation Learning. AISTATS.

Preprint PDF Project Video

E. Saucan, M. Weber (2019). Forman's Ricci curvature - From networks to hypernetworks. Complex Networks and Their Applications.

Preprint PDF Project

M. Weber, J. Jost, E. Saucan (2018). Detecting the Coarse Geometry of Networks. NeurIPS R2L.

Preprint Project

M. Weber, M. Nickel (2018). Curvature and Representation Learning: Identifying Embedding Spaces for Relational Data. NeurIPS R2L.

M. Weber, E. Saucan, J. Jost (2018). Coarse Geometry of Evolving Networks. Journal of Complex Networks.

Preprint PDF Project

E. Saucan, A. Samal, M. Weber, J. Jost (2018). Discrete Curvatures and Network Analysis. MATCH.

M. Weber, E. Saucan, J. Jost (2017). Characterizing complex networks with Forman-Ricci curvature and associated geometric flows. Journal of Complex Networks.

Preprint PDF Project

M. Weber, P. M. Maia, J. N. Kutz (2017). Estimating Memory Deterioration Rates Following Neurodegeneration and Traumatic Brain Injuries in a Hopfield Network Model. Frontiers in Neuroscience.

Preprint PDF Code

M. Weber, J. Stelzer, E. Saucan, A. Naitsat, G. Lohmann, J. Jost (2017). Curvature-based Methods for Brain Network Analysis. Technical Report.

Preprint Project

S. Ballouz *, M. Weber, P. Pavlidis, J. Gillis (2016). EGAD: Ultra-fast Functional Analysis of Gene Networks. Bioinformatics.

Preprint PDF Code

M. Weber (2016). Event Classification with Convolutional Neural Networks for Diboson Channels in the ATLAS Experiment at the Large Hadron Collider. Undergraduate Thesis, TU Dresden.

M. Weber (2016). Forman-Ricci Curvature and Associated Geometric Flows for Complex Networks. Undergraduate Thesis, U Leipzig.

M. Weber, J. Jost, E. Saucan (2016). Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets. Axioms.

Preprint PDF Project