106 citations · 252 across the 33 of their papers we have counts for
35 papers
Bayesian Feature Extraction using Gaussian and Diffused-gamma Priors for High Dimensional Spatio-Temporal Data
Garrett Frady, Dipak K. Dey, Shariq Mohammed
High-dimensional data with sparse structure and spatio-temporal dependence arise in many scientific domains. We develop a Bayesian feature-extraction framework for spatio-temporal…
Scalable spatial point process models for forensic footwear analysis
Alokesh Manna, Neil Spencer, Dipak K. Dey
Shoe print evidence recovered from crime scenes plays a key role in forensic investigations. By examining shoe prints, investigators can determine details of the footwear worn by s…
Distribution-free inference for LightGBM and GLM with Tweedie loss
Alokesh Manna, Aditya Vikram Sett, Dipak K. Dey +3
Prediction uncertainty quantification is a key research topic in recent years scientific and business problems. In insurance industries (\cite{parodi2023pricing}), assessing the ra…
Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
Alokesh Manna, Zijian Huang, Dipak K. Dey +2
The Tweedie exponential dispersion family is a popular choice among many to model insurance losses that consist of zero-inflated semicontinuous data. In such data, it is often impo…
Generalized Variable Selection Algorithms for Gaussian Process Models by LASSO-like Penalty
Zhiyong Hu, Dipak Dey
With the rapid development of modern technology, massive amounts of data with complex pattern are generated. Gaussian process models that can easily fit the non-linearity in data b…
Improving Opioid Use Disorder Risk Modelling through Behavioral and Genetic Feature Integration
Sybille Légitime, Kaustubh Prabhu, Devin McConnell +3
Opioids are an effective analgesic for acute and chronic pain, but also carry a considerable risk of addiction leading to millions of opioid use disorder (OUD) cases and tens of th…