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ORCIDMelanie Weber 0001
Person information
- affiliation: Harvard University, USA
- affiliation (former): University of Oxford, UK
- affiliation (former): Princeton University, NJ, USA
Other persons with the same name
- Melanie Weber
- Melanie Weber 0002 — German Aerospace Center, Institute of Transportation Systems, Berlin, Germany
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2020 – today
- 2026
[i41]Knut Vanderbush, Melanie Weber:
Neural Algorithmic Reasoning for Approximate k-Coloring with Recursive Warm Starts. CoRR abs/2601.05137 (2026)- 2025
- [j8]Melanie Weber
:
Geometric Machine Learning. AI Mag. 46(1) (2025) - [j7]Yu Tian, Zachary Lubberts, Melanie Weber:
Curvature-based Clustering on Graphs. J. Mach. Learn. Res. 26: 52:1-52:67 (2025) - [c14]Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb:
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. ICLR 2025 - [c13]Menglin Yang, Yifei Zhang, Jialin Chen, Melanie Weber, Rex Ying:
Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks. WWW (Companion Volume) 2025: 1811-1814 - [i40]Raphael Pellegrin, Lukas Fesser, Melanie Weber:
Enhancing the Utility of Higher-Order Information in Relational Learning. CoRR abs/2502.09570 (2025) - [i39]Lukas Fesser, Melanie Weber:
Performance Heterogeneity in Graph Neural Networks: Lessons for Architecture Design and Preprocessing. CoRR abs/2503.00547 (2025) - [i38]Andrew Lee, Melanie Weber, Fernanda B. Viégas, Martin Wattenberg:
Shared Global and Local Geometry of Language Model Embeddings. CoRR abs/2503.21073 (2025) - [i37]Neil He, Jiahong Liu, Buze Zhang, Ngoc Bui, Ali Maatouk, Menglin Yang, Irwin King, Melanie Weber, Rex Ying:
Position: Beyond Euclidean - Foundation Models Should Embrace Non-Euclidean Geometries. CoRR abs/2504.08896 (2025) - [i36]Menglin Yang, Yifei Zhang, Jialin Chen, Melanie Weber, Rex Ying:
Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks. CoRR abs/2505.14417 (2025) - [i35]Imran Nasim, Melanie Weber:
Automated Manifold Learning for Reduced Order Modeling. CoRR abs/2506.01741 (2025) - [i34]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia S. Dong, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutierrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - [i33]Nicolás Hinrichs, Noah Guzmán, Melanie Weber:
On a Geometry of Interbrain Networks. CoRR abs/2509.10650 (2025) - [i32]Annabel Ma, Kaiying Hou, David Alvarez-Melis, Melanie Weber:
Bispectral OT: Dataset Comparison using Symmetry-Aware Optimal Transport. CoRR abs/2509.20678 (2025) - [i31]Moritz Hehl, Max von Renesse, Melanie Weber:
Neural Feature Geometry Evolves as Discrete Ricci Flow. CoRR abs/2509.22362 (2025) - [i30]Willem Diepeveen, Melanie Weber:
Iso-Riemannian Optimization on Learned Data Manifolds. CoRR abs/2510.21033 (2025) - [i29]Ekdeep Singh Lubana, Can Rager, Sai Sumedh R. Hindupur, Valérie Costa, Greta Tuckute, Oam Patel, Sonia Krishna Murthy, Thomas Fel, Daniel Wurgaft, Eric J. Bigelow, Johnny Lin, Demba E. Ba, Martin Wattenberg, Fernanda B. Viégas, Melanie Weber, Aaron Mueller:
Priors in Time: Missing Inductive Biases for Language Model Interpretability. CoRR abs/2511.01836 (2025) - [i28]Behrooz Tahmasebi, Melanie Weber:
Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry. CoRR abs/2512.11855 (2025) - 2024
- [j6]Amy Feng, Melanie Weber:
Graph Pooling via Ricci Flow. Trans. Mach. Learn. Res. 2024 (2024) - [c12]Melanie Weber:
Exploiting Data Geometry in Machine Learning. AAAI 2024: 22681 - [c11]Andrew Cheng, Melanie Weber:
Structured Regularization for SPD Optimization with Side Information. Allerton 2024: 1-8 - [c10]Lukas Fesser, Melanie Weber:
Effective Structural Encodings via Local Curvature Profiles. ICLR 2024 - [c9]Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber:
On the hardness of learning under symmetries. ICLR 2024 - [c8]Bobak T. Kiani, Lukas Fesser, Melanie Weber:
Unitary Convolutions for Learning on Graphs and Groups. NeurIPS 2024 - [c7]Bobak T. Kiani, Jason Wang, Melanie Weber:
Hardness of Learning Neural Networks under the Manifold Hypothesis. NeurIPS 2024 - [i27]Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber:
On the hardness of learning under symmetries. CoRR abs/2401.01869 (2024) - [i26]Bobak T. Kiani, Jason Wang, Melanie Weber:
Hardness of Learning Neural Networks under the Manifold Hypothesis. CoRR abs/2406.01461 (2024) - [i25]Amy Feng, Melanie Weber:
Graph Pooling via Ricci Flow. CoRR abs/2407.04236 (2024) - [i24]Andrew Cheng, Vaibhav Dixit, Melanie Weber:
Disciplined Geodesically Convex Programming. CoRR abs/2407.05261 (2024) - [i23]Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb:
Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. CoRR abs/2410.02698 (2024) - [i22]Bobak T. Kiani, Lukas Fesser, Melanie Weber:
Unitary convolutions for learning on graphs and groups. CoRR abs/2410.05499 (2024) - [i21]Andrew Cheng, Melanie Weber:
Structured Regularization for Constrained Optimization on the SPD Manifold. CoRR abs/2410.09660 (2024) - 2023
- [j5]Melanie Weber, Suvrit Sra:
Riemannian Optimization via Frank-Wolfe Methods. Math. Program. 199(1): 525-556 (2023) - [c6]Melanie Weber, Suvrit Sra:
Global optimality for Euclidean CCCP under Riemannian convexity. ICML 2023: 36790-36803 - [c5]Lukas Fesser, Melanie Weber:
Mitigating Over-Smoothing and Over-Squashing Using Augmentations of Forman-Ricci Curvature. LoG 2023: 19 - [i20]Lukas Fesser, Sergio Serrano de Haro Iváñez, Karel Devriendt, Melanie Weber, Renaud Lambiotte:
Augmentations of Forman's Ricci Curvature and their Applications in Community Detection. CoRR abs/2306.06474 (2023) - [i19]Nicolás García Trillos, Melanie Weber:
Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds. CoRR abs/2307.02378 (2023) - [i18]Yu Tian, Zachary Lubberts, Melanie Weber:
Curvature-based Clustering on Graphs. CoRR abs/2307.10155 (2023) - [i17]Lukas Fesser, Melanie Weber:
Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature. CoRR abs/2309.09384 (2023) - [i16]Lukas Fesser, Melanie Weber:
Effective Structural Encodings via Local Curvature Profiles. CoRR abs/2311.14864 (2023) - 2022
- [c4]Yu Tian, Zachary Lubberts, Melanie Weber:
Mixed-membership community detection via line graph curvature. NeurReps 2022: 219-233 - [i15]Suvrit Sra, Melanie Weber:
On a class of geodesically convex optimization problems solved via Euclidean MM methods. CoRR abs/2206.11426 (2022) - [i14]Melanie Weber, Suvrit Sra:
Computing Brascamp-Lieb Constants through the lens of Thompson Geometry. CoRR abs/2208.05013 (2022) - [i13]Wenyue Hua, Yuchen Zhang, Zhe Chen, Josie Li, Melanie Weber:
LegalRelectra: Mixed-domain Language Modeling for Long-range Legal Text Comprehension. CoRR abs/2212.08204 (2022) - 2021
- [b1]Melanie Weber:
On Geometric Optimization, Learning and Control. Princeton University, USA, 2021 - [i12]Jackson Sargent, Melanie Weber:
Identifying biases in legal data: An algorithmic fairness perspective. CoRR abs/2109.09946 (2021) - 2020
- [c3]Melanie Weber:
Neighborhood Growth Determines Geometric Priors for Relational Representation Learning. AISTATS 2020: 266-276 - [c2]Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar:
Robust large-margin learning in hyperbolic space. NeurIPS 2020 - [i11]Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar:
Robust Large-Margin Learning in Hyperbolic Space. CoRR abs/2004.05465 (2020)
2010 – 2019
- 2019
- [i10]Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan MacDonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber:
The Oracle of DLphi. CoRR abs/1901.05744 (2019) - [i9]Melanie Weber, Suvrit Sra:
Nonconvex stochastic optimization on manifolds via Riemannian Frank-Wolfe methods. CoRR abs/1910.04194 (2019) - [i8]Melanie Weber:
Neighborhood Growth Determines Geometric Priors for Relational Representation Learning. CoRR abs/1910.05565 (2019) - 2018
- [j4]Melanie Weber, Emil Saucan, Jürgen Jost:
Coarse geometry of evolving networks. J. Complex Networks 6(5): 706-732 (2018) - [c1]Emil Saucan, Melanie Weber:
Forman's Ricci Curvature - From Networks to Hypernetworks. COMPLEX NETWORKS (1) 2018: 706-717 - [i7]F. Patricia Medina, Linda Ness, Melanie Weber, Karamatou Yacoubou Djima:
Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis. CoRR abs/1807.00349 (2018) - [i6]Emil Saucan, Melanie Weber:
Forman's Ricci curvature - From networks to hypernetworks. CoRR abs/1810.07749 (2018) - 2017
- [j3]Sara Ballouz, Melanie Weber, Paul Pavlidis, Jesse A. Gillis:
EGAD: ultra-fast functional analysis of gene networks. Bioinform. 33(4): 612-614 (2017) - [j2]Melanie Weber, Emil Saucan, Jürgen Jost:
Characterizing complex networks with Forman-Ricci curvature and associated geometric flows. J. Complex Networks 5(4): 527-550 (2017) - [i5]Melanie Weber, Johannes Stelzer, Emil Saucan, Alexander Naitsat, Gabriele Lohmann, Jürgen Jost:
Curvature-based Methods for Brain Network Analysis. CoRR abs/1707.00180 (2017) - [i4]Melanie Weber, Suvrit Sra:
Frank-Wolfe methods for geodesically convex optimization with application to the matrix geometric mean. CoRR abs/1710.10770 (2017) - 2016
- [j1]Melanie Weber, Jürgen Jost, Emil Saucan:
Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets. Axioms 5(4): 26 (2016) - [i3]Melanie Weber, Jürgen Jost, Emil Saucan:
Forman-Ricci flow for change detection in large dynamic data sets. CoRR abs/1604.06634 (2016) - [i2]Melanie Weber, Emil Saucan, Jürgen Jost:
Characterizing Complex Networks with Forman-Ricci Curvature and Associated Geometric Flows. CoRR abs/1607.08654 (2016) - [i1]Melanie Weber, Emil Saucan, Jürgen Jost:
Can one see the shape of a network? CoRR abs/1608.07838 (2016)
Coauthor Index
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