A Cognac shot to forget bad memories: Corrective Unlearning in GNNs

1 code implementation • 1 Dec 2024 • Varshita Kolipaka, Akshit Sinha, Debangan Mishra, Sumit Kumar, Arvindh Arun, Shashwat Goel, Ponnurangam Kumaraguru

To allow model developers to remove the adverse effects of manipulated entities from a trained GNN, we study the recently formulated problem of Corrective Unlearning.

Ensemble of Task-Specific Language Models for Brain Encoding

1 code implementation • 24 Oct 2023 • Arvindh Arun, Jerrin John, Sanjai Kumaran

Language models have been shown to be rich enough to encode fMRI activations of certain Regions of Interest in our Brains.

Transfer Learning

CAFIN: Centrality Aware Fairness inducing IN-processing for Unsupervised Representation Learning on Graphs

1 code implementation • 10 Apr 2023 • Arvindh Arun, Aakash Aanegola, Amul Agrawal, Ramasuri Narayanam, Ponnurangam Kumaraguru

Unsupervised Representation Learning on graphs is gaining traction due to the increasing abundance of unlabelled network data and the compactness, richness, and usefulness of the representations generated.

Fairness Graph Learning +3