5 citations · 7 across the 3 of their papers we have counts for
4 papers
Cause and Effect: Can Large Language Models Truly Understand Causality?
Swagata Ashwani, Kshiteesh Hegde, Nishith Reddy Mannuru +6
With the rise of Large Language Models(LLMs), it has become crucial to understand their capabilities and limitations in deciphering and explaining the complex web of causal relatio…
Network Lens: Node Classification in Topologically Heterogeneous Networks
Kshiteesh Hegde, Malik Magdon-Ismail
We study the problem of identifying different behaviors occurring in different parts of a large heterogenous network. We zoom in to the network using lenses of different sizes to c…
The Intrinsic Scale of Networks is Small
Malik Magdon-Ismail, Kshiteesh Hegde
We define the intrinsic scale at which a network begins to reveal its identity as the scale at which subgraphs in the network (created by a random walk) are distinguishable from si…
Network Signatures from Image Representation of Adjacency Matrices: Deep/Transfer Learning for Subgraph Classification
Kshiteesh Hegde, Malik Magdon-Ismail, Ram Ramanathan +1
We propose a novel subgraph image representation for classification of network fragments with the targets being their parent networks. The graph image representation is based on 2D…