2 citations · 5 across the 6 of their papers we have counts for
7 papers
Machine Unlearning for Causal Inference
Vikas Ramachandra, Mohit Sethi
Machine learning models play a vital role in making predictions and deriving insights from data and are being increasingly used for causal inference. To preserve user privacy, it i…
Weather event severity prediction using buoy data and machine learning
Vikas Ramachandra
In this paper, we predict severity of extreme weather events (tropical storms, hurricanes, etc.) using buoy data time series variables such as wind speed and air temperature. The p…
Deep Clustering for Mars Rover image datasets
Vikas Ramachandra
In this paper, we build autoencoders to learn a latent space from unlabeled image datasets obtained from the Mars rover. Then, once the latent feature space has been learnt, we use…
Forecasting the effect of heat stress index and climate change on cloud data center energy consumption
Vikas Ramachandra
In this paper, we estimate the effect of heat stress index (a measure which takes into account rising temperatures as well as humidity) on data center energy consumption. We use fo…
Causal inference for climate change events from satellite image time series using computer vision and deep learning
Vikas Ramachandra
We propose a method for causal inference using satellite image time series, in order to determine the treatment effects of interventions which impact climate change, such as defore…
Causal Inference for Survival Analysis
Vikas Ramachandra
In this paper, we propose the use of causal inference techniques for survival function estimation and prediction for subgroups of the data, upto individual units. Tree ensemble met…