DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization

1 code implementation • 20 Dec 2023 • Aritra Bhowmick, Mert Kosan, Zexi Huang, Ambuj Singh, Sourav Medya

Graph clustering is a fundamental and challenging task in the field of graph mining where the objective is to group the nodes into clusters taking into consideration the topology of the graph.

Clustering Graph Clustering +2

LipBaB: Computing exact Lipschitz constant of ReLU networks

no code implementations • 12 May 2021 • Aritra Bhowmick, Meenakshi D'Souza, G. Srinivasa Raghavan

The Lipschitz constant of neural networks plays an important role in several contexts of deep learning ranging from robustness certification and regularization to stability analysis of systems with neural network controllers.