10 citations · 11 across the 2 of their papers we have counts for
7 papers
Search for Lorentz Invariance Violation from stacked Gamma-Ray Burst spectral lag data
Rajdeep Agrawal, Haveesh Singirikonda, Shantanu Desai
A number of works have claimed detections of a turn-over in the spectral lag data for individual Gamma-Ray Bursts (GRBs), caused by an energy-dependent speed of light, which could…
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond
Charles C. Margossian, Aki Vehtari, Daniel Simpson +1
Gaussian latent variable models are a key class of Bayesian hierarchical models with applications in many fields. Performing Bayesian inference on such models can be challenging as…
Covariance Matrix Estimation under Total Positivity for Portfolio Selection
Raj Agrawal, Uma Roy, Caroline Uhler
Selecting the optimal Markowitz porfolio depends on estimating the covariance matrix of the returns of assets from periods of historical data. Problematically, is typic…
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
Brian L. Trippe, Jonathan H. Huggins, Raj Agrawal +1
Due to the ease of modern data collection, applied statisticians often have access to a large set of covariates that they wish to relate to some observed outcome. Generalized linea…
ABCD-Strategy: Budgeted Experimental Design for Targeted Causal Structure Discovery
Raj Agrawal, Chandler Squires, Karren Yang +2
Determining the causal structure of a set of variables is critical for both scientific inquiry and decision-making. However, this is often challenging in practice due to limited in…
Data-dependent compression of random features for large-scale kernel approximation
Raj Agrawal, Trevor Campbell, Jonathan H. Huggins +1
Kernel methods offer the flexibility to learn complex relationships in modern, large data sets while enjoying strong theoretical guarantees on quality. Unfortunately, these methods…