347 citations · 795 across the 48 of their papers we have counts for
7 papers · 1 filter
Crop Planning using Stochastic Visual Optimization
Gunjan Sehgal, Bindu Gupta, Kaushal Paneri +3
As the world population increases and arable land decreases, it becomes vital to improve the productivity of the agricultural land available. Given the weather and soil properties,…
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks
Narendhar Gugulothu, Vishnu TV, Pankaj Malhotra +3
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assump…
Comparative Benchmarking of Causal Discovery Techniques
Karamjit Singh, Garima Gupta, Vartika Tewari +1
In this paper we present a comprehensive view of prominent causal discovery algorithms, categorized into two main categories (1) assuming acyclic and no latent variables, and (2) a…
TimeNet: Pre-trained deep recurrent neural network for time series classification
Pankaj Malhotra, Vishnu TV, Lovekesh Vig +2
Inspired by the tremendous success of deep Convolutional Neural Networks as generic feature extractors for images, we propose TimeNet: a deep recurrent neural network (RNN) trained…
A complex network analysis of ethnic conflicts and human rights violations
Kiran Sharma, Gunjan Sehgal, Bindu Gupta +4
News reports in media contain records of a wide range of socio-economic and political events in time. Using a publicly available, large digital database of news records, and aggreg…
Minimally-Supervised Attribute Fusion for Data Lakes
Karamjit Singh, Garima Gupta, Gautam Shroff +1
Aggregate analysis, such as comparing country-wise sales versus global market share across product categories, is often complicated by the unavailability of common join attributes,…
Deep Convolutional Neural Networks for Pairwise Causality
Karamjit Singh, Garima Gupta, Lovekesh Vig +2
Discovering causal models from observational and interventional data is an important first step preceding what-if analysis or counterfactual reasoning. As has been shown before, th…