Melanie Weber
Melanie Weber
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Effective Structural Encodings via Local Curvature Profiles
Structural and Positional Encodings can significantly improve the performance of Graph Neural Networks in downstream tasks. Recent …
L. Fesser
,
M. Weber
PDF
Project
On the Hardness of Learning under Symmetries
We study the problem of learning equivariant neural networks via gradient descent. The incorporation of known symmetries …
B. T. Kiani
,
T. Le
,
H. Lawrence
,
S. Jegelka
,
M. Weber
PDF
Project
Mitigating Over-Smoothing and Over-Squashing using Augmentations of Forman-Ricci Curvature
While Graph Neural Networks (GNNs) have been successfully leveraged for learning on graph-structured data across domains, several …
L. Fesser
,
M. Weber
PDF
Project
Sampling Informative Positives Pairs in Contrastive Learning
Contrastive Learning is a paradigm for learning representation functions that recover useful similarity structure in a dataset based on …
M. Weber
,
P. Bachman
PDF
Project
Global optimality for Euclidean CCCP under Riemannian convexity
We study geodesically convex (g-convex) problems that can be written as a difference of Euclidean convex functions. This structure …
M. Weber
,
S. Sra
Preprint
Project
LegalRelectra: Mixed-domain Language Modeling for Long-range Legal Text Comprehension
The application of Natural Language Processing (NLP) to specialized domains, such as the law, has recently received a surge of …
W. Hua
,
Y. Zhang
,
Z. Chen
,
J. Li
,
M. Weber
PDF
Mixed-Membership Community Detection via Line Graph Curvature
Community detection is a classical method for understanding the structure of relational data. In this paper, we study the problem of …
Y. Tian
,
Z. Lubberts
,
M. Weber
PDF
Project
Identifying biases in legal data: An algorithmic fairness perspective
The need to address representation biases and sentencing disparities in legal case data has long been recognized. Here, we study the …
J. Sargent
,
M. Weber
Preprint
Robust Large-Margin Learning in Hyperbolic Space
Recently, there has been a surge of interest in representation learning in hyperbolic spaces, driven by their ability to represent …
M. Weber
,
M. Zaheer
,
A. Singh Rawat
,
A. Menon
,
S. Kumar
Preprint
PDF
Project
Video
Neighborhood Growth Determines Geometric Priors for Relational Representation Learning
The problem of identifying geometric structure in heterogeneous, high-dimensional data is a cornerstone of representation learning. …
M. Weber
Preprint
PDF
Project
Video
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