Melanie Weber

Orcid: 0000-0003-1104-7181

Affiliations:
  • Harvard University, USA
  • University of Oxford, UK (former)
  • Princeton University, NJ, USA (former)


According to our database1, Melanie Weber authored at least 33 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Unitary convolutions for learning on graphs and groups.
CoRR, 2024

Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups.
CoRR, 2024

Disciplined Geodesically Convex Programming.
CoRR, 2024

Graph Pooling via Ricci Flow.
CoRR, 2024

Hardness of Learning Neural Networks under the Manifold Hypothesis.
CoRR, 2024

On the hardness of learning under symmetries.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Effective Structural Encodings via Local Curvature Profiles.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Exploiting Data Geometry in Machine Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Riemannian Optimization via Frank-Wolfe Methods.
Math. Program., May, 2023

Curvature-based Clustering on Graphs.
CoRR, 2023

Continuum Limits of Ollivier's Ricci Curvature on data clouds: pointwise consistency and global lower bounds.
CoRR, 2023

Augmentations of Forman's Ricci Curvature and their Applications in Community Detection.
CoRR, 2023

Mitigating Over-Smoothing and Over-Squashing Using Augmentations of Forman-Ricci Curvature.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Global optimality for Euclidean CCCP under Riemannian convexity.
Proceedings of the International Conference on Machine Learning, 2023

2022
LegalRelectra: Mixed-domain Language Modeling for Long-range Legal Text Comprehension.
CoRR, 2022

Computing Brascamp-Lieb Constants through the lens of Thompson Geometry.
CoRR, 2022

On a class of geodesically convex optimization problems solved via Euclidean MM methods.
CoRR, 2022

Mixed-membership community detection via line graph curvature.
Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

2021
On Geometric Optimization, Learning and Control
PhD thesis, 2021

Identifying biases in legal data: An algorithmic fairness perspective.
CoRR, 2021

2020
Robust large-margin learning in hyperbolic space.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neighborhood Growth Determines Geometric Priors for Relational Representation Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
Nonconvex stochastic optimization on manifolds via Riemannian Frank-Wolfe methods.
CoRR, 2019

The Oracle of DLphi.
CoRR, 2019

2018
Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis.
CoRR, 2018

Coarse geometry of evolving networks.
J. Complex Networks, 2018

Forman's Ricci Curvature - From Networks to Hypernetworks.
Proceedings of the Complex Networks and Their Applications VII, 2018

2017
Frank-Wolfe methods for geodesically convex optimization with application to the matrix geometric mean.
CoRR, 2017

Curvature-based Methods for Brain Network Analysis.
CoRR, 2017

Characterizing complex networks with Forman-Ricci curvature and associated geometric flows.
J. Complex Networks, 2017

EGAD: ultra-fast functional analysis of gene networks.
Bioinform., 2017

2016
Can one see the shape of a network?
CoRR, 2016

Forman-Ricci Flow for Change Detection in Large Dynamic Data Sets.
Axioms, 2016


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