7 citations · 15 across the 6 of their papers we have counts for
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stat.ML2015★ 2 cited
Sparse Pseudo-input Local Kriging for Large Spatial Datasets with Exogenous Variables
Babak Farmanesh, Arash Pourhabib
We study large-scale spatial systems that contain exogenous variables, e.g. environmental factors that are significant predictors in spatial processes. Building predictive models f…
stat.ML2015★ 7 cited
A Bayesian framework for functional calibration of expensive computational models through non-isometric matching
Babak Farmanesh, Arash Pourhabib, Balabhaskar Balasundaram +1
We study statistical calibration, i.e., adjusting features of a computational model that are not observable or controllable in its associated physical system. We focus on functiona…
stat.ML2015★ 2 cited
Empirical Similarity for Absent Data Generation in Imbalanced Classification
Arash Pourhabib
When the training data in a two-class classification problem is overwhelmed by one class, most classification techniques fail to correctly identify the data points belonging to the…