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cs.LG2025

LLM-driven Knowledge Distillation for Dynamic Text-Attributed Graphs

Amit Roy, Ning Yan, Masood Mortazavi

Dynamic Text-Attributed Graphs (DyTAGs) have numerous real-world applications, e.g. social, collaboration, citation, communication, and review networks. In these networks, nodes an…

cs.LG2021

Unified Spatio-Temporal Modeling for Traffic Forecasting using Graph Neural Network

Amit Roy, Kashob Kumar Roy, Amin Ahsan Ali +2

Research in deep learning models to forecast traffic intensities has gained great attention in recent years due to their capability to capture the complex spatio-temporal relations…

cs.LG2021

Node Embedding using Mutual Information and Self-Supervision based Bi-level Aggregation

Kashob Kumar Roy, Amit Roy, A K M Mahbubur Rahman +2

Graph Neural Networks (GNNs) learn low dimensional representations of nodes by aggregating information from their neighborhood in graphs. However, traditional GNNs suffer from two…

cs.LG2021

Structure-Aware Hierarchical Graph Pooling using Information Bottleneck

Kashob Kumar Roy, Amit Roy, A K M Mahbubur Rahman +2

Graph pooling is an essential ingredient of Graph Neural Networks (GNNs) in graph classification and regression tasks. For these tasks, different pooling strategies have been propo…

cs.LG2021

SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network

Amit Roy, Kashob Kumar Roy, Amin Ahsan Ali +2

To capture spatial relationships and temporal dynamics in traffic data, spatio-temporal models for traffic forecasting have drawn significant attention in recent years. Most of the…