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Sarthak Malik

2 accepted papers

2025

SALE-MLP: Structure Aware Latent Embeddings for GNN to Graph-free MLP Distillation

IJCAI 2025

Graph Neural Networks (GNNs), with their ability to effectively handle non-Euclidean data structures, have demonstrated state-of-the-art performance in learning node and graph-level representations. However, GNNs face significant computational overhead due to their message-passing mechanisms, making

2024

CPa-WAC: Constellation Partitioning-based Scalable Weighted Aggregation Composition for Knowledge Graph Embedding

IJCAI 2024poster

Scalability and training time are crucial for any graph neural network model processing a knowledge graph (KG). While partitioning knowledge graphs helps reduce the training time, the prediction accuracy reduces significantly compared to training the model on the whole graph. In this paper, we propo…