28 citations · 48 across the 4 of their papers we have counts for
5 papers
Faster Optimization on Sparse Graphs via Neural Reparametrization
Nima Dehmamy, Csaba Both, Jianzhi Long +1
In mathematical optimization, second-order Newton's methods generally converge faster than first-order methods, but they require the inverse of the Hessian, hence are computational…
Automatic Symmetry Discovery with Lie Algebra Convolutional Network
Nima Dehmamy, Robin Walters, Yanchen Liu +2
Existing equivariant neural networks require prior knowledge of the symmetry group and discretization for continuous groups. We propose to work with Lie algebras (infinitesimal gen…
3D Topology Transformation with Generative Adversarial Networks
Luca Stornaiuolo, Nima Dehmamy, Albert-László Barabási +1
Generation and transformation of images and videos using artificial intelligence have flourished over the past few years. Yet, there are only a few works aiming to produce creative…
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
Chintan Shah, Nima Dehmamy, Nicola Perra +4
Locating the source of an epidemic, or patient zero (P0), can provide critical insights into the infection's transmission course and allow efficient resource allocation. Existing m…
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
Nima Dehmamy, Albert-László Barabási, Rose Yu
To deepen our understanding of graph neural networks, we investigate the representation power of Graph Convolutional Networks (GCN) through the looking glass of graph moments, a ke…