6 citations · 6 across the 3 of their papers we have counts for
4 papers
A Probabilistic Framework for Knowledge Graph Data Augmentation
Jatin Chauhan, Priyanshu Gupta, Pasquale Minervini
We present NNMFAug, a probabilistic framework to perform data augmentation for the task of knowledge graph completion to counter the problem of data scarcity, which can enhance the…
Target Model Agnostic Adversarial Attacks with Query Budgets on Language Understanding Models
Jatin Chauhan, Karan Bhukar, Manohar Kaul
Despite significant improvements in natural language understanding models with the advent of models like BERT and XLNet, these neural-network based classifiers are vulnerable to bl…
Learning Representations using Spectral-Biased Random Walks on Graphs
Charu Sharma, Jatin Chauhan, Manohar Kaul
Several state-of-the-art neural graph embedding methods are based on short random walks (stochastic processes) because of their ease of computation, simplicity in capturing complex…
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
Deepak Nathani, Jatin Chauhan, Charu Sharma +1
The recent proliferation of knowledge graphs (KGs) coupled with incomplete or partial information, in the form of missing relations (links) between entities, has fueled a lot of re…