6 citations · 6 across the 14 of their papers we have counts for
4 papers · 1 filter
Path Laplacian Encodings for Directed Graphs
Lydia Mezrag, Semih Cantürk, Michael Perlmutter +2
Directed graphs naturally model many real-world systems in which interactions are asymmetric, such as citation networks, web graphs, and information-flow networks. However, graph l…
RhinoNet: Unsupervised Learning for Phenoscaping and Generation of High Dimensional Point Clouds
Siddharth Viswanath, Hiren Madhu, Eddie Cavallin +7
We present RhinoNet, a simplicial complex-based point cloud neural network, that creates a geometry-preserving embedding of high-dimensional point clouds. RhinoNet takes collection…
BrainDyn: A Sheaf Neural ODE for Forecasting and Generating Brain Dynamics
Siddharth Viswanath, Panayiotis Ketonis, Chen Liu +11
Brain activity unfolds as coordinated patterns across regions over time, and modeling these dynamics is a central goal in computational neuroscience. Because activity is distribute…
Can Computational Reducibility Lead to Transferable Models for Graph Combinatorial Optimization?
Semih Cantürk, Thomas Sabourin, Frederik Wenkel +2
A key challenge in developing unified neural solvers for combinatorial optimization (CO) is the efficient generalization of models from a given set of tasks to new tasks unseen dur…