We study the ability of transformer-based language models (LMs) to under...
We propose temporal Poisson square root graphical models (TPSQRs), a
gen...
We study the L_1-regularized maximum likelihood estimator/estimation (ML...
A popular way to estimate the causal effect of a variable x on y from
ob...
The widespread digitization of patient data via electronic health record...
We present a simple text mining method that is easy to implement, requir...
The pseudo-likelihood method is one of the most popular algorithms for
l...
Computational Drug Repositioning (CDR) is the task of discovering potent...