46 citations · 157 across the 12 of their papers we have counts for
12 papers
Complex Logical Reasoning over Knowledge Graphs using Large Language Models
Nurendra Choudhary, Chandan K. Reddy
Reasoning over knowledge graphs (KGs) is a challenging task that requires a deep understanding of the complex relationships between entities and the underlying logic of their relat…
Text Enriched Sparse Hyperbolic Graph Convolutional Networks
Nurendra Choudhary, Nikhil Rao, Karthik Subbian +1
Heterogeneous networks, which connect informative nodes containing text with different edge types, are routinely used to store and process information in various real-world applica…
Towards Scalable Hyperbolic Neural Networks using Taylor Series Approximations
Nurendra Choudhary, Chandan K. Reddy
Hyperbolic networks have shown prominent improvements over their Euclidean counterparts in several areas involving hierarchical datasets in various domains such as computer vision,…
A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
Mehrdad Khatir, Nurendra Choudhary, Sutanay Choudhury +2
Hyperbolic neural networks can effectively capture the inherent hierarchy of graph datasets, and consequently a powerful choice of GNNs. However, they entangle multiple incongruent…
Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya +2
Logical reasoning over Knowledge Graphs (KGs) is a fundamental technique that can provide efficient querying mechanism over large and incomplete databases. Current approaches emplo…
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya +2
Knowledge Graphs (KGs) are ubiquitous structures for information storagein several real-world applications such as web search, e-commerce, social networks, and biology. Querying KG…
Cross-Lingual Task-Specific Representation Learning for Text Classification in Resource Poor Languages
Nurendra Choudhary, Rajat Singh, Manish Shrivastava
Neural network models have shown promising results for text classification. However, these solutions are limited by their dependence on the availability of annotated data. The pros…
Contrastive Learning of Emoji-based Representations for Resource-Poor Languages
Nurendra Choudhary, Rajat Singh, Ishita Bindlish +1
The introduction of emojis (or emoticons) in social media platforms has given the users an increased potential for expression. We propose a novel method called Classification of Em…
Sentiment Analysis of Code-Mixed Languages leveraging Resource Rich Languages
Nurendra Choudhary, Rajat Singh, Ishita Bindlish +1
Code-mixed data is an important challenge of natural language processing because its characteristics completely vary from the traditional structures of standard languages. In this…
Emotions are Universal: Learning Sentiment Based Representations of Resource-Poor Languages using Siamese Networks
Nurendra Choudhary, Rajat Singh, Ishita Bindlish +1
Machine learning approaches in sentiment analysis principally rely on the abundance of resources. To limit this dependence, we propose a novel method called Siamese Network Archite…
Automatic Normalization of Word Variations in Code-Mixed Social Media Text
Rajat Singh, Nurendra Choudhary, Manish Shrivastava
Social media platforms such as Twitter and Facebook are becoming popular in multilingual societies. This trend induces portmanteau of South Asian languages with English. The blend…
Neural Network Architecture for Credibility Assessment of Textual Claims
Nurendra Choudhary, Rajat Singh, Ishita Bindlish +1
Text articles with false claims, especially news, have recently become aggravating for the Internet users. These articles are in wide circulation and readers face difficulty discer…