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Melanie Weber

9 papers at tracked venues · 8 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. Data Augmentation: A Fourier Analysis Perspective
  2. Higher-Order Learning with Graph Neural Networks via Hypergraph Encodings
  3. Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
  4. Towards Non-Euclidean Foundation Models: Advancing AI Beyond Euclidean Frameworks
  5. Effective Structural Encodings via Local Curvature Profiles
  6. Exploiting Data Geometry in Machine Learning
    AAAI 2024 · Melanie Weber
  7. Hardness of Learning Neural Networks under the Manifold Hypothesis
  8. On the hardness of learning under symmetries
  9. Unitary Convolutions for Learning on Graphs and Groups