Search Results for author: M. Narasimha Murty

Found 7 papers, 1 papers with code

Higher-Order Relations Skew Link Prediction in Graphs

no code implementations30 Oct 2021 Govind Sharma, Aditya Challa, Paarth Gupta, M. Narasimha Murty

In this article, we investigate this problem in the presence of higher-order relations.

Link Prediction

The CAT SET on the MAT: Cross Attention for Set Matching in Bipartite Hypergraphs

1 code implementation30 Oct 2021 Govind Sharma, Swyam Prakash Singh, V. Susheela Devi, M. Narasimha Murty

Usual relations between entities could be captured using graphs; but those of a higher-order -- more so between two different types of entities (which we term "left" and "right") -- calls for a "bipartite hypergraph".

Link Prediction set matching

Decentralised Approach for Multi Agent Path Finding

no code implementations3 Jun 2021 Shyni Thomas, M. Narasimha Murty

Multi Agent Path Finding (MAPF) requires identification of conflict free paths for agents which could be point-sized or with dimensions.

Multi-Agent Path Finding Scheduling

Robust Hierarchical Graph Classification with Subgraph Attention

no code implementations19 Jul 2020 Sambaran Bandyopadhyay, Manasvi Aggarwal, M. Narasimha Murty

Towards this end, we propose a graph classification algorithm called SubGattPool which jointly learns the subgraph attention and employs two different types of hierarchical attention mechanisms to find the important nodes in a hierarchy and the importance of individual hierarchies in a graph.

General Classification Graph Classification

Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization

no code implementations8 Jun 2020 Sambaran Bandyopadhyay, Manasvi Aggarwal, M. Narasimha Murty

Invent of graph neural networks has improved the state-of-the-art for both node and the entire graph representation in a vector space.

Graph Classification Representation Learning

Finding Influential Institutions in Bibliographic Information Networks

no code implementations27 Dec 2016 Anubhav Gupta, M. Narasimha Murty

The KDD Cup $2016$ competition considers one such problem, which is to measure the impact of research institutions, i. e. to perform ranking of research institutions.

Social and Information Networks Information Retrieval

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