Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (with an oral spotlight!) at ML4H Workshop, NeurIPS 2020.

Implementation for the paper: Representation Learning on Knowledge Graphs for Node Importance Estimation

[EMNLP'21 Findings] HyperExpan: Taxonomy Expansion with Hyperbolic Representation Learning

Data structure detection with neural networks.

Improving Heterogeneus Graph Transformer archiecture exploiting structural information of graph

This repository is for managing our work on anomaly detection in financial services using knowledge graphs and machine learning for the CADS internship during the month of July 2021.

Social Computing with Deep Graph Library (DGL)