5 papers
Contextual Tokenization for Graph Inverted Indices
Pritish Chakraborty, Indradyumna Roy, Soumen Chakrabarti +1
Retrieving graphs from a large corpus, that contain a subgraph isomorphic to a given query graph, is a core operation in many real-world applications. While recent multi-vector gra…
Charting the Design Space of Neural Graph Representations for Subgraph Matching
Vaibhav Raj, Indradyumna Roy, Ashwin Ramachandran +2
Subgraph matching is vital in knowledge graph (KG) question answering, molecule design, scene graph, code and circuit search, etc. Neural methods have shown promising results for s…
Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval
Ashwin Ramachandran, Vaibhav Raj, Indrayumna Roy +2
Graph retrieval based on subgraph isomorphism has several real-world applications such as scene graph retrieval, molecular fingerprint detection and circuit design. Roy et al. [35]…
Graph Regularized Encoder Training for Extreme Classification
Anshul Mittal, Shikhar Mohan, Deepak Saini +10
Deep extreme classification (XC) aims to train an encoder architecture and an accompanying classifier architecture to tag a data point with the most relevant subset of labels from…
Graph Edit Distance with General Costs Using Neural Set Divergence
Eeshaan Jain, Indradyumna Roy, Saswat Meher +2
Graph Edit Distance (GED) measures the (dis-)similarity between two given graphs, in terms of the minimum-cost edit sequence that transforms one graph to the other. However, the ex…