Melanie Weber - RankMe

65 papers A* 8A 1Journal 50Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Neural Algorithmic Reasoning for Approximate k-Coloring with Recursive Warm Starts. CoRR Knut Vanderbush, Melanie Weber
2026	J	`jnl`	Protein Graph Neural Networks for Heterogeneous Cryo-EM Reconstruction. CoRR Jonathan Krook, Axel Janson, Joakim Andén, Melanie Weber, Ozan Öktem
2025	J	`jnl`	Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry. CoRR Behrooz Tahmasebi, Melanie Weber
2025	J	`jnl`	Automated Manifold Learning for Reduced Order Modeling. CoRR Imran Nasim, Melanie Weber
2025	J	`jnl`	Bispectral OT: Dataset Comparison using Symmetry-Aware Optimal Transport. CoRR Annabel Ma, Kaiying Hou, David Alvarez-Melis, Melanie Weber
2025	J	`jnl`	Curvature-based Clustering on Graphs. J. Mach. Learn. Res. Yu Tian, Zachary Lubberts, Melanie Weber
2025	J	`jnl`	Enhancing the Utility of Higher-Order Information in Relational Learning. CoRR Raphael Pellegrin, Lukas Fesser, Melanie Weber
2025	J	`jnl`	Geometric Machine Learning. AI Mag. Melanie Weber
2025	J	`jnl`	Iso-Riemannian Optimization on Learned Data Manifolds. CoRR Willem Diepeveen, Melanie Weber
2025	A*	`conf`	Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. ICLR Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb
2025	J	`jnl`	Neural Feature Geometry Evolves as Discrete Ricci Flow. CoRR Moritz Hehl, Max von Renesse, Melanie Weber
2025	J	`jnl`	On a Geometry of Interbrain Networks. CoRR Nicolás Hinrichs, Noah Guzmán, Melanie Weber
2025	J	`jnl`	Performance Heterogeneity in Graph Neural Networks: Lessons for Architecture Design and Preprocessing. CoRR Lukas Fesser, Melanie Weber
2025	J	`jnl`	Position: Beyond Euclidean - Foundation Models Should Embrace Non-Euclidean Geometries. CoRR Neil He, Jiahong Liu, Buze Zhang, Ngoc Bui, Ali Maatouk, Menglin Yang, Irwin King, Melanie Weber, Rex Ying
2025	J	`jnl`	Priors in Time: Missing Inductive Biases for Language Model Interpretability. CoRR 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
2025	J	`jnl`	Shared Global and Local Geometry of Language Model Embeddings. CoRR Andrew Lee, Melanie Weber, Fernanda B. Viégas, Martin Wattenberg
2025	J	`jnl`	The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR 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
2025	—	`conf`	Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks. WWW (Companion Volume) Menglin Yang, Yifei Zhang, Jialin Chen, Melanie Weber, Rex Ying
2025	J	`jnl`	Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks. CoRR Menglin Yang, Yifei Zhang, Jialin Chen, Melanie Weber, Rex Ying
2024	J	`jnl`	Disciplined Geodesically Convex Programming. CoRR Andrew Cheng, Vaibhav Dixit, Melanie Weber
2024	A*	`conf`	Effective Structural Encodings via Local Curvature Profiles. ICLR Lukas Fesser, Melanie Weber
2024	A*	`conf`	Exploiting Data Geometry in Machine Learning. AAAI Melanie Weber
2024	J	`jnl`	Graph Pooling via Ricci Flow. CoRR Amy Feng, Melanie Weber
2024	J	`jnl`	Graph Pooling via Ricci Flow. Trans. Mach. Learn. Res. Amy Feng, Melanie Weber
2024	A*	`conf`	Hardness of Learning Neural Networks under the Manifold Hypothesis. NeurIPS Bobak T. Kiani, Jason Wang, Melanie Weber
2024	J	`jnl`	Hardness of Learning Neural Networks under the Manifold Hypothesis. CoRR Bobak T. Kiani, Jason Wang, Melanie Weber
2024	J	`jnl`	Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups. CoRR Zakhar Shumaylov, Peter Zaika, James Rowbottom, Ferdia Sherry, Melanie Weber, Carola-Bibiane Schönlieb
2024	A*	`conf`	On the hardness of learning under symmetries. ICLR Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
2024	J	`jnl`	On the hardness of learning under symmetries. CoRR Bobak T. Kiani, Thien Le, Hannah Lawrence, Stefanie Jegelka, Melanie Weber
2024	J	`jnl`	Structured Regularization for Constrained Optimization on the SPD Manifold. CoRR Andrew Cheng, Melanie Weber
2024	—	`conf`	Structured Regularization for SPD Optimization with Side Information. Allerton Andrew Cheng, Melanie Weber
2024	A*	`conf`	Unitary Convolutions for Learning on Graphs and Groups. NeurIPS Bobak T. Kiani, Lukas Fesser, Melanie Weber
2024	J	`jnl`	Unitary convolutions for learning on graphs and groups. CoRR Bobak T. Kiani, Lukas Fesser, Melanie Weber
2023	J	`jnl`	Augmentations of Forman's Ricci Curvature and their Applications in Community Detection. CoRR Lukas Fesser, Sergio Serrano de Haro Iváñez, Karel Devriendt, Melanie Weber, Renaud Lambiotte
2023	J	`jnl`	Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds. CoRR Nicolás García Trillos, Melanie Weber
2023	J	`jnl`	Curvature-based Clustering on Graphs. CoRR Yu Tian, Zachary Lubberts, Melanie Weber
2023	J	`jnl`	Effective Structural Encodings via Local Curvature Profiles. CoRR Lukas Fesser, Melanie Weber
2023	A*	`conf`	Global optimality for Euclidean CCCP under Riemannian convexity. ICML Melanie Weber, Suvrit Sra
2023	—	`conf`	Mitigating Over-Smoothing and Over-Squashing Using Augmentations of Forman-Ricci Curvature. LoG Lukas Fesser, Melanie Weber
2023	J	`jnl`	Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature. CoRR Lukas Fesser, Melanie Weber
2023	J	`jnl`	Riemannian Optimization via Frank-Wolfe Methods. Math. Program. Melanie Weber, Suvrit Sra
2022	J	`jnl`	Computing Brascamp-Lieb Constants through the lens of Thompson Geometry. CoRR Melanie Weber, Suvrit Sra
2022	J	`jnl`	LegalRelectra: Mixed-domain Language Modeling for Long-range Legal Text Comprehension. CoRR Wenyue Hua, Yuchen Zhang, Zhe Chen, Josie Li, Melanie Weber
2022	—	`conf`	Mixed-membership community detection via line graph curvature. NeurReps Yu Tian, Zachary Lubberts, Melanie Weber
2022	J	`jnl`	On a class of geodesically convex optimization problems solved via Euclidean MM methods. CoRR Suvrit Sra, Melanie Weber
2021	J	`jnl`	Identifying biases in legal data: An algorithmic fairness perspective. CoRR Jackson Sargent, Melanie Weber
2021	—	`—`	On Geometric Optimization, Learning and Control Melanie Weber
2020	A	`conf`	Neighborhood Growth Determines Geometric Priors for Relational Representation Learning. AISTATS Melanie Weber
2020	J	`jnl`	Robust Large-Margin Learning in Hyperbolic Space. CoRR Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2020	A*	`conf`	Robust large-margin learning in hyperbolic space. NeurIPS Melanie Weber, Manzil Zaheer, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
2019	J	`jnl`	Neighborhood Growth Determines Geometric Priors for Relational Representation Learning. CoRR Melanie Weber
2019	J	`jnl`	Nonconvex stochastic optimization on manifolds via Riemannian Frank-Wolfe methods. CoRR Melanie Weber, Suvrit Sra
2019	J	`jnl`	The Oracle of DLphi. CoRR 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
2018	J	`jnl`	Coarse geometry of evolving networks. J. Complex Networks Melanie Weber, Emil Saucan, Jürgen Jost
2018	—	`conf`	Forman's Ricci Curvature - From Networks to Hypernetworks. COMPLEX NETWORKS (1) Emil Saucan, Melanie Weber
2018	J	`jnl`	Forman's Ricci curvature - From networks to hypernetworks. CoRR Emil Saucan, Melanie Weber
2018	J	`jnl`	Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis. CoRR F. Patricia Medina, Linda Ness, Melanie Weber, Karamatou Yacoubou Djima
2017	J	`jnl`	Characterizing complex networks with Forman-Ricci curvature and associated geometric flows. J. Complex Networks Melanie Weber, Emil Saucan, Jürgen Jost
2017	J	`jnl`	Curvature-based Methods for Brain Network Analysis. CoRR Melanie Weber, Johannes Stelzer, Emil Saucan, Alexander Naitsat, Gabriele Lohmann, Jürgen Jost
2017	J	`jnl`	EGAD: ultra-fast functional analysis of gene networks. Bioinform. Sara Ballouz, Melanie Weber, Paul Pavlidis, Jesse A. Gillis
2017	J	`jnl`	Frank-Wolfe methods for geodesically convex optimization with application to the matrix geometric mean. CoRR Melanie Weber, Suvrit Sra
2016	J	`jnl`	Can one see the shape of a network? CoRR Melanie Weber, Emil Saucan, Jürgen Jost
2016	J	`jnl`	Characterizing Complex Networks with Forman-Ricci Curvature and Associated Geometric Flows. CoRR Melanie Weber, Emil Saucan, Jürgen Jost
2016	J	`jnl`	Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets. Axioms Melanie Weber, Jürgen Jost, Emil Saucan
2016	J	`jnl`	Forman-Ricci flow for change detection in large dynamic data sets. CoRR Melanie Weber, Jürgen Jost, Emil Saucan