While Graph Neural Networks (GNNs) have been successfully leveraged for
...
Unsupervised node clustering (or community detection) is a classical gra...
Let ℳ⊆ℝ^d denote a low-dimensional manifold
and let 𝒳= { x_1, …, x_n } b...
The notion of curvature on graphs has recently gained traction in the
ne...
The application of Natural Language Processing (NLP) to specialized doma...
This paper studies algorithms for efficiently computing Brascamp-Lieb
co...
We study geodesically convex (g-convex) problems that can be written as ...
The need to address representation biases and sentencing disparities in ...
Recently, there has been a surge of interest in representation learning ...
The problem of identifying geometric structure in heterogeneous,
high-di...
We study stochastic projection-free methods for constrained optimization...
We present a novel technique based on deep learning and set theory which...
Networks and their higher order generalizations, such as hypernetworks o...
When analyzing empirical data, we often find that global linear models
o...