1 code implementation • 7 Nov 2022 • Max Wasserman, Gonzalo Mateos
Implementations of differentiable graph structure learning models are written in PyTorch, allowing us to leverage the rich software ecosystem that exists e. g., around logging, hyperparameter search, and GPU-communication.
no code implementations • 19 May 2022 • Max Wasserman, Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro
Machine learning frameworks such as graph neural networks typically rely on a given, fixed graph to exploit relational inductive biases and thus effectively learn from network data.