265 citations · 280 across the 6 of their papers we have counts for
6 papers
Relation Matters in Sampling: A Scalable Multi-Relational Graph Neural Network for Drug-Drug Interaction Prediction
Arthur Feeney, Rishabh Gupta, Veronika Thost +4
Sampling is an established technique to scale graph neural networks to large graphs. Current approaches however assume the graphs to be homogeneous in terms of relations and ignore…
SEMIE: SEMantically Infused Embeddings with Enhanced Interpretability for Domain-specific Small Corpus
Rishabh Gupta, Rajesh N Rao
Word embeddings are a basic building block of modern NLP pipelines. Efforts have been made to learn rich, efficient, and interpretable embeddings for large generic datasets availab…
Evaluation of deep learning models for multi-step ahead time series prediction
Rohitash Chandra, Shaurya Goyal, Rishabh Gupta
Time series prediction with neural networks has been the focus of much research in the past few decades. Given the recent deep learning revolution, there has been much attention in…
Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdown
Animesh Tiwari, Rishabh Gupta, Rohitash Chandra
Air pollution has a wide range of implications on agriculture, economy, road accidents, and health. In this paper, we use novel deep learning methods for short-term (multi-step-ahe…
Towards Semantic Noise Cleansing of Categorical Data based on Semantic Infusion
Rishabh Gupta, Rajesh N Rao
Semantic Noise affects text analytics activities for the domain-specific industries significantly. It impedes the text understanding which holds prime importance in the critical de…
DiffQue: Estimating Relative Difficulty of Questions in Community Question Answering Services
Deepak Thukral, Adesh Pandey, Rishabh Gupta +2
Automatic estimation of relative difficulty of a pair of questions is an important and challenging problem in community question answering (CQA) services. There are limited studies…